Coin Metrics’ State of the Network: Issue 57 – Introducing Free Float Supply

Introducing Free Float Supply

By Ben Celermajer and the Coin Metrics Team

Key Takeaways

  • Until now, a standardized approach to determining the free float supply (the supply that is available to the market) of cryptoassets has not been established. This has hindered the market from developing a clear understanding of available supply and market capitalization.
  • Coin Metrics’ free float supply takes many of the best practices from traditional capital markets and applies them to cryptoassets to identify supply that is highly unlikely to be available to the market in the short to mid-term. In doing so, free float supply provides a better approximation of a cryptoasset’s liquidity and market capitalization. 
  • Index weighting can benefit from using free float supply – free float supply reflects the liquid market more accurately and reduces potential manipulability.
  • Tracking free float supply provides insight into primary token holder behavior. This can lead to more transparent reporting of foundation and team selling, increased knowledge of total market supply and behavioral analysis of stakeholders.
  • Many cryptoasset valuation metrics use market capitalization which primarily utilize the on-chain visible supply. Deriving these metrics with a free float capitalization may improve the signal achieved.

Introduction

In April, Coin Metrics announced a new methodology for the determination of a cryptoasset’s supply that is ‘available’ to the market, cryptoasset free float.

Without reporting standards and regulations that require foundations and companies to accurately report holdings in a timely manner, obtaining supply data that is reflective of market trading opportunities can be a challenge.

Coin Metrics’ free float supply takes many of the best practices from traditional capital markets and applies them to cryptoassets to identify supply that is unlikely to be available to the market. In doing so, free float supply provides a better approximation of a cryptoasset’s liquidity and market capitalization. For more information on the supply that is considered restricted, please refer to the CMBI Adjusted Free Float Methodology.

While initially created to help inform CMBI design, cryptoasset free float supply can be applied in many different ways to help market participants make smarter investment decisions. Some of the areas where free float can be applied to improve market understanding include:

  • Market Capitalization
  • Indexes
  • Valuation methods
  • Foundation and Founding Team Transparency

Applying Free Float to Market Capitalization

Typically, investors expect a market size measurement to reflect the total value of assets that are available in the market. For example, to determine market capitalization in equity markets, data providers and participants exclude company and executive team owned shares, as well as shares owned by other strategic investment partners that do not provide liquidity to markets. 

A standardized approach like this has not yet been consistently applied to determining the free float supply and market capitalization of cryptoassets. This has hindered the market from developing a clear understanding of available supply and market capitalization.

For determining supply and market capitalization, the CMBI Adjusted Free Float Methodology applies a standardized criteria for which units of supply to exclude from free float, including but not limited to:

  • Supply owned by foundations, companies and founding teams
  • Supply in addresses that have been inactive for over 5 years
  • Supply staked in a smart contract to partake in governance and long-term strategic outcomes of a network without any direct monetary incentive to do so
  • Supply that is vesting on-chain
  • Supply that is burned or provably lost

Applying the above methodology rigorously to the top cryptoassets identifies a more comprehensive supply that is not available to the market. Utilizing the available supply to trade (free float supply) rather than either reported supply by foundations/companies or total visible on-chain supply can significantly impact investor’s understanding of the total market size of a cryptoasset and related metrics such as dominance and liquidity.

Evidenced in the above, standard industry reporting of cryptoasset supply, and thus market capitalization, has traditionally been overstated. Some of the more pertinent examples of this are:

  • Bitcoin – where the industry standard has been 18.4M. Coin Metrics free float calculations determine that a more accurate representation of free float supply is 14.3M (22% lower), reflecting that 4.1M Bitcoin has not been transacted in over 5 years and as such can be considered to be owned by long term strategic holders that do not provide liquidity to markets (or lost).
  • Bitcoin Cash and Bitcoin SV – the industry standard has been to utilize their on-chain supply of ~18.5M native units to determine market capitalization. Through understanding how many BCH and BSV have been moved since the fork, Coin Metrics has determined that a more accurate representation of supply for BCH and BSV is 12.0M (36% lower) and 9.9M (45% lower) respectively. 
  • XRP and Stellar – both of these foundations report their own holdings to data distributors. Due to an absence of regulatory standards and the irregularity of reporting, not all addresses may be disclosed and the reported values may not be maintained. Coin Metrics has identified additional supply that can be traced to the foundations and team members, which is reflected by XRP and Stellar having a free float supply of 30.4B and 16.5B, lower than is typically reported.

Applying Free Float to Indexes

Most multi asset indexes are weighted by each constituent asset’s market capitalization. Thus, redefining a cryptoasset market capitalization to reflect free float will impact the construction of indexes.

The key benefits of weighting an index using the free float market capitalization as opposed to the reported market capitalization include: reflecting the liquid market more accurately, maintaining more timely supply data to weight indexes, reducing potential manipulability of index weightings, and reducing index rebalancing costs.

Cryptoassets have varying levels of auditability and transparency when it comes to foundation and team holdings. For this reason, Coin Metrics applies a free float supply banding approach when weighting CMBI Indexes. The banding methodology reflects that supply determination is currently not a perfect science. For example if Coin Metrics identify 53% of cryptoassets as the free float supply, but the ‘true’ value is 56% (or 50%), the asset will ultimately fall into the 50-60% band. Such an approach helps to overcome nuances in supply determination and varying levels of transparency, reporting and auditability.

Simply, after determining the ratio of free float to on-chain available supply, each asset’s ratio is rounded up to the closest 10%. This value is then applied for the purpose of weighting assets in the CMBI Market Cap Weighted Asset Index Series. For example:

  1. Bitcoin’s free float ratio is 77.8% (free float supply of 14.3M of a total on-chain supply of 18.4M). 
  2. Rounded up to the nearest 10%, Bitcoin’s band would be 80%
  3. Applied to the total supply of Bitcoin, 18.4M, Bitcoin’s in weight in the index would be derived using a supply of 14.7M (18.4M * 80%)

Increasing Market Transparency

As part of Coin Metrics’ new free float supply metric identification process, addresses in the following categories have been tagged by Coin Metrics and are considered to be restricted: 

  • Owned by foundations/companies
  • Owned by founding team members
  • Governance contracts where there is no direct financial benefit
  • Provably lost 

Doing so can provide timely and transparent reporting of the movements and actions of each category of stakeholder on a cryptoasset’s network. This can lead to more transparent reporting of foundation and team selling, increased knowledge of total market supply and behavioral analysis of stakeholders.

Without transparency, market participants are left uninformed on the actions of foundations and teams, making it impossible to understand the holistic market dynamics. 

Case Study 1: Tether (USDT)

Many market spectators monitor and observe the printing and burning of USDT as significant market events that can impact the price of Bitcoin and crypto markets. Speculation to the impacts of Tether activity has been so high that many academics and regulators have investigated this activity during significant market events. 

However, observing the on-chain activity of USDT can be misleading as Tether has historically printed USDT in large batches in anticipation of future demand and distributions. Thus, on-chain supply does not necessarily mean new supply in public markets. Coin Metrics’ free float supply excludes USDT held by the Tether Treasury to provide a more accurate indication of the supply that is currently in public markets.

As can be observed below, particularly through 2018 and the first half of 2019, the USDT issued does not necessarily represent the USDT in markets. Particularly interesting is the USDT activity in early 2019. Market participants observing the on-chain supply would not have noticed significant change as Bitcoin rose from $4,000 to $12,000. However, by observing free float supply, the correlation between free float USDT and Bitcoin’s price becomes clearer.

Continue Reading…

Continue reading “Introducing Free Float Supply,” including analysis of how free float supply can be used to improve valuation metrics.

Network Data Insights

Summary Metrics

Ethereum (ETH) activity surged again this past week, driven by the rise of DeFi applications like Compound as well as the continued growth of stablecoins. ETH active addresses grew another 8.4% week-over-week and have now reached their highest levels of 2020. Transactions also continue to grow at a fast rate. On average, there were over a million daily ETH transactions over the past week. ETH daily transaction fees grew another 26.4% week-over-week, bringing ETH’s average fees over the last week to $663.9K compared to $322.2K for BTC. 

Despite the large growth in usage and economic metrics, ETH market cap did not significantly outperform over the last week – it only grew by 0.8%, compared to a 0.9% dip for BTC. 

Network Highlights

About 40M units of 0x (ZRX) have entered free float supply since the middle of June. ZRX free float supply increased from 631.5M on June 13th to 671.4M on June 27th. 

As introduced in today’s Weekly Feature, free float supply provides a better approximation of a cryptoasset’s liquidity and market capitalization by measuring the amount of supply that is freely available to the market. The large increase in ZRX free float supply is because the ZRX foundation has started using treasury funds to yield farm on Compound, contributing the 40M ZRX to liquidity pools.

Basic Attention Token (BAT) free float supply has increased by about 10M since the beginning of June, as some BAT team members have also looked to benefit from Compound farming.

ZRX and BAT have both also seen an uptick in transactions in May and June. There were over 13.63K BAT transactions on June 27th, a new all-time high. The following chart is smoothed using a 7 day rolling average. 

Market Data Insights

While certain network activity may be trending up, spot market volume has continued to decline over the past month due to the dampening of volatility. In the analysis below we look at the change in aggregate volume from  Binance, Binance.us, Bitfinex, Bitflyer, Bitstamp, Bittrex, Coinbase’ FTX, Gemini, Huobi, itBit, Kraken, Kucoin, Okex, Poloniex and Upbit.

Bitcoin volume has been trending down over the past 30 days, nearly reaching levels not seen since the larger sell off in mid-march. This pattern correlates with falling ranges of volatility that we noted prior this month

0x, on the other hand, did recently reach a relative peak in terms of daily volume. During June the project’s 30 day average volume increased roughly 560% to ~$33m from ~$5m following the momentum of the DeFi craze.

Basic Attention token also saw an increase in trading volume, however it was not as extreme. The recent DeFi demand brought an uptick in trading but it did not surpass the volumes seen between March and May 2019. This prior uplift was largely due to product releases from the Brave team surrounding their Brave Rewards and Advertising platform.

CM Bletchley Indexes (CMBI) Insights

This week was very similar to the last, with most CMBI and Bletchley Indexes slightly down for the week. The Bletchley 40 was the only exception of the market cap weighted indexes, finishing up 4.2%. 

The strength in small-cap assets this week can be further observed through the positive returns of the Bletchley Total Even Index. Despite the slightly negative returns of the Bletchley 10 and Bletchley 20, when the 70 constituents of the Bletchley universe each receive a weight of 1.43%, the return for the week is positive.

The CMBI Bitcoin Index and CMBI Ethereum Index continue to range trade and experience historically low levels of volatility, finishing the week down 3.1% and 1.7% respectively.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

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Coin Metrics’ State of the Network: Issue 56 – Do Coinbase Listings Turn Altcoins Into Gold?

Digital Alchemy: Do Coinbase Listings Turn Altcoins Into Gold?

By Jon Geenty and the Coin Metrics Team

Key Takeaways

  • A Coinbase listing has historically shown, not surprisingly, to have a positive impact on listed assets’ prices immediately following the announcement.
  • The uplift from a listing is more muted than some may perceive, with the average and median uplift ranging from roughly -1% to 14% against US Dollar, Bitcoin and Ethereum benchmarks. Price trends seen with assets such as the recent OmiseGo listing are outliers. 
  • Coinbase’s ‘Exploration’ announcements tend to have less of a direct impact on mentioned asset’s prices. The price movements surrounding these events are less significant and largely related to the general market regime at time of announcement. We compare these changes in a bearish, bullish and flat market using past examples.

Does a Coinbase Listing Always Deliver Results?

With the recent rise in altcoin prices and volumes, it is as good a time as any to discuss a phenomenon that typically elicits a lot of trading activity: The Coinbase listing.

Exchanges with a significant amount of market share at times can be “king makers” for altcoins. The simple suggestion or rumor that you will be listed on a top exchange has the potential to turn a valueless crypto “bag” into a large profit. Binance, Bittrex and Poloniex are exchanges known for listing the long tail of altcoins, but what about Coinbase?  

With the industry consensus being that Coinbase is the largest ‘retail’ onramp, the impact of a Coinbase listing should hold some significance on assets that might make the cut. However there is another big factor that influences the impact of the listing: market conditions. 

In this piece, we explore three separate instances that Coinbase announced they would be exploring new assets for potential listing, and analyze how the assets performed afterwards. Additionally, we explore the market conditions at time of announcement, and how different market environments (bear vs. flat vs. bull) impact the listings. 

Source: Coin Metrics Reference Rates

Methodology

For details on the methodology used in this piece see the full-length report on the Coin Metrics blog.

The Impact of the Possibility of Listing

December 2018 – Bear Market

On December 7, 2018, Coinbase announced the ‘exploration’ of 31 assets for potential listing.  The below chart shows the median and mean performance for the mentioned group against different benchmarks. 

Prior to that announcement the assets were generally tumbling in price. It is important to put in context of the asset class, with the 25 day prior mark being mid-November 2018.  During this period, Bitcoin sold off from ~$6,350 to ~$3,200, the lowest range that we have seen since the 2017 peak. This is reflected in the following chart, which shows asset price change in USD.

This announcement date precedes this “bottom” by a few days. In the period following these assets saw rebounds in value and over the following 100 days appreciated generally 50% in price against Bitcoin. The histogram below displays how the appreciation changed over time, from a tightly distributed decline in the 10 days immediately following the post to a broader, more positive distribution over the following 100 days.

August 2019 – Flat, Choppy Market

The group of assets in the second ‘exploration’ blog post in August 2019 was a much smaller sample size than the first, with only eight assets.

The market environment had also changed significantly. In this period Bitcoin had just hit 2019 highs in July and was trading in a choppy range between $12k and $8k, trending down. 

Continue Reading

Continue reading the full article including analysis of the June 2020 blog post and impact of actual listings.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

On June 9th and 10th ETH daily transaction fees soared past BTC daily fees due to two transactions that each inexplicably spent $2.6M on transaction fees (as covered in the Network Data section of State of the Network Issue 55). Although there is still confusion around the exact reason for the high fees, the sender has been revealed to be South Korean based peer-to-peer exchange Good Cycle. 

ETH fees appear to be down because there were no more anomalous transactions this week, and therefore this week’s fee totals pale in comparison to last week’s. But ETH fees have actually been trending upwards over the last few weeks, as explored in this week’s Network Highlights section.

Network Highlights

Over the last two weeks ETH has flipped BTC in terms of daily transaction fees. Despite the obvious outliers due to the two mysterious transactions, ETH fees have continued to top BTC’s following June 10th. The last time that ETH fees topped BTC fees for at least 14 consecutive days was July 2018.  

Source: Coin Metrics Network Data Pro

Although ETH total fees have surged, BTC median fees are still higher than ETH median fees. Over the last week, BTC median fees have fluctuated between about $1 and $1.50, while ETH median fees have remained between $0.47 and $0.65. ETH median fees have, however, grown significantly since the beginning of the year. On January 1st, 2020, ETH median fees were a little less than $0.04. 

Source: Coin Metrics Network Data Pro

ETH blocks have also been getting increasingly full over the last few weeks. Relatively full blocks shows that there’s demand to use the network. To address the increase in block fullness, on June 20th Ethereum miners voted to increase the network’s gas limit by 25%. This is reflected in the following chart, which shows both the gas limit per block and the gas used per block.

Source: Coin Metrics Network Data Pro

Market Data Insights

The Compound Effect 

While the overall market has remained little changed over the past month with volatility near record lows for this market cycle, Compound’s launch of their governance token has ignited interest in the decentralized finance space. The amount of collateral locked within the Compound platform has surpassed Maker due to their implementation of liquidity mining — paying out a certain amount of Compound tokens to borrowers and lenders on the platform. 

Compound token’s rapid price growth has been reflected in most other DeFi tokens such as Aave, Maker, Bancor, and Kyber Network. This is suggestive of behavior last seen during the ICO-driven market bubble, although Ren and 0x’s muted price performance indicates that some rationality persists. 

While financial asset bubbles in mature markets are generally undesirable, financial bubbles in rapidly emerging markets such as DeFi can be a good thing in the long-run because it can incentive the build out of additional infrastructure that normally would not be economical. 

Source: Coin Metrics Reference Rates

Tether Supply Growth is Slowing

Since the beginning of the coronavirus-related lockdowns, Tether supply growth has been extremely strong. Here we show Tether’s free float supply, a measure of supply that represents the amount of supply freely available for purchase by investors. Notably, it excludes Tether that has been issued but not yet released. This year, a fairly steady rate of growth brought total Tether free float supply from around 5 billion units to 9 billion units. In just the past few weeks, however, Tether supply growth has slowed considerably, although it is still positive. 

Source: Coin Metrics Network Data Pro

Although the assumption that Tether is fully backed by fiat currency is tenuous and not fully proven, one interpretation of Tether supply growth is that it represents new capital inflows into the space. The common narrative is that Tether is printed, sent to exchanges, and then used to purchase Bitcoin or other cryptoassets. Here we plot one-month Bitcoin price growth with one-month Tether supply growth to examine the connection. Recent data points to a tight correlation between the two time series. As Tether supply growth has slowed, Bitcoin’s price growth has also attenuated.

CM Bletchley Indexes (CMBI) Insights

CMBI and Bletchley Indexes had a relatively flat week with the exception of the Bletchley 40 (small-cap) Index which closed the week up 7.4%. The CMBI Bitcoin Index and the CMBI Ethereum Index both closed the week slightly down, falling 0.6% and 2.2% respectively. 

With the CMBI Bitcoin Index down near historically low volatility levels, the large and mid-cap markets seem to be awaiting Bitcoin to make its next move before experiencing too much action. However, small-cap assets have performed independently and strongly this month, with the Bletchley 40 up 15% already. The Bletchley 10 and Bletchley 20 have seen little action, returning -2.5% and 0.1% respectively.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

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Coin Metrics’ State of the Network: Issue 55 – Assessing Crypto’s Recovery Three Months After The March 12th Crash

Assessing Crypto’s Recovery Three Months After The March 12th Crash

By Nate Maddrey and and the Coin Metrics Team

Key Takeaways

  • Bitcoin (BTC) and Ether (ETH) have recovered most of their losses after the March 12th crash, while assets like Bitcoin Cash (BCH) and Litecoin (LTC) have lagged behind.
  • Other assets that have outperformed include Cardano (ADA), Crypto.com Coin (CRO), and OmiseGO (OMG).
  • Stablecoin trading volume has exploded since March 12th, with Tether (USDT) leading the way. BTC-USDT spot market volume on Binance, Bitfinex, Bittrex, HitBTC, Huobi, and LBank shot up to new highs on March 13th, and has remained relatively elevated since.
  • Volume continued to spike in April and May on all six exchanges, although to a lesser extent than on March 13th.
  • Another trend that has emerged following March 12th is the growth of addresses holding relatively small amounts of crypto. Since March 12th, BTC and ETH have both had noticeable increases in addresses holding at least 1 billionth of total supply. 

Introduction

On March 12th crypto experienced one of its largest crashes ever with many assets falling over 50% in less than 24 hours. Now, a little more than three months later, the market has turned around and shown signs of recovery. However, not all assets have reacted equally, and the market continues to change at a fast pace as global uncertainty remains high.

In today’s Weekly Feature we look at network data (i.e. on-chain data) and market data to assess how different assets recovered, and analyze some of the ongoing changes after the crash. 

Price Recovery Differs Across Assets

Assets like Bitcoin (BTC) and Ether (ETH) have recovered most of their losses after the crash, while other assets like Bitcoin Cash (BCH) and Litecoin (LTC) have lagged behind.

The below chart shows market capitalization for nine major cryptoassets over the last year. All nine assets experienced market cap spikes in February, immediately prior to the crash. BTC’s market cap reached $188.76B on February 14th, its highest point in 2020. ETH’s 2020 market cap peaked at $31.25B, also on February 14th.

After the crash, BTC’s market cap recovered to $187.58B by June 1st 2020, just shy of its February high. Similarly, ETH’s market cap reached $27.69B on June 1st.

But other assets have not recovered as much of their pre-crash highs. BCH’s post-crash market cap peaked at $4.92B on April 8th, down from $9.01B on February 14th. LTC market cap reached $5.37B on February 14th and has not passed $3.2B since. Ripple (XRP) and Bitcoin SV (BSV) are also down compared to other assets.

Source: Coin Metrics Network Data Pro

Price recovery paints a similar picture. The below chart shows price recovery (i.e. percent regained of initial price) from February 14th, which was the high point for many cryptoassets in 2020, to June 14th. 

In addition to BTC and ETH, several mid-cap assets like Cardano (ADA) and Crypto.com Coin (CRO) have recovered relatively well. OmiseGO (OMG), which launched on Coinbase Pro on May 19th, has also outperformed.

Source: Coin Metrics Reference Rates

Stablecoin Trading Volume Has Surged

Stablecoin trading volume has exploded since March 12th, with Tether (USDT) leading the way. BTC-USDT spot market volume on Binance, Bitfinex, Bittrex, HitBTC, Huobi, and LBank shot up to new highs on March 13th, and has remained relatively elevated since. Volume continued to spike in April and May on all six exchanges, although to a lesser extent than on March 13th.

The following chart shows BTC-USDT trading volume smoothed using a 7-day rolling average.

Source: Coin Metrics Market Data Feed

This increase in volume corresponds with the huge growth in Tether supply seen since February 2020. Tether is currently issued on many different platforms, including Ethereum (USDT_ETH) and Tron (USDT_TRX). USDT_ETH supply more than doubled from February to May 2020, and USDT_TRX supply has more than tripled over the last two months. 

Source: Coin Metrics Network Data Pro

Addresses Holding Small Amounts of BTC and ETH are Growing

Another trend that has emerged following March 12th is the growth of addresses holding relatively small amounts of crypto. 

The following chart shows the number of addresses holding at least 1 billionth of total supply (.000000001%). BTC and ETH both had noticeable increases in growth following March 12th. Ripple (XRP) and Tezos (XTZ) have also shown steady growth over the last year. This suggests that the amount of individuals holding these assets is growing, and that the amount of retail investors (i.e. non-institutional) may be increasing. 

However, it’s important to note that a single entity can own many addresses at once, so an increase in addresses does not necessarily mean an increase in usage. Alternatively, the rise could be caused by a small number of entities spreading their coins across many addresses.

Source: Coin Metrics Network Data Pro

Conclusion

In three short months after the March 12th crash BTC and ETH have recovered most of their losses. Additionally, stablecoin trading volume has exploded, and the amount of addresses holding small amounts of BTC and ETH have grown. However, not all assets have recovered as well as BTC and ETH. BCH and LTC market caps remain well below 2020 highs, and many other assets are lagging as well. 

As global uncertainty is still high, it remains to be seen whether crypto will continue to trend upwards. But at least up to this point, a lot of the post-crash data has pointed towards a relatively strong recovery.

Check out our free community charting tool to access some of the data used in this piece as well as more of our on-chain network data.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) and Ethereum (ETH) both had slightly down yet relatively stable weeks. BTC’s market capitalization dropped 1.8% week-over-week, while ETH’s dropped 1.3%. Realized capitalization (which values each coin at the last time it moved on-chain), however, increased for both.

Notably, ETH daily fees grew by over 178.5% week-over-week, a seemingly huge surge. However, this was due to two specific transactions which each inexplicably spent $2.6M on transaction fees

Bitcoin Cash (BCH) and Litecoin (LTC) continued their downward trends as highlighted in today’s Weekly Feature. LTC active addresses dropped 15.8% week-over-week. Although BCH addresses increased 11.3% week-over-week, most other BCH on-chain metrics were down, including a 46.8% drop in transactions.

Network Highlights

There were 1.05M Bitcoin daily active addresses on June 11th, the highest single day total of 2020. Bitcoin daily active addresses have not topped 1.05M since June 2019. 

Source: Coin Metrics Network Data Pro

Bitcoin active addresses also surged in May. Current levels of active addresses have only been seen twice before in Bitcoin’s history: December 2017, when Bitcoin price was approaching $20K, and July 2019, when Bitcoin’s price climbed from around $5K to over $13K. The following chart shows Bitcoin daily active addresses since May 2015, smoothed using a 7-day rolling average.

Source: Coin Metrics Network Data Pro

Ethereum daily active addresses have also surged in the past few weeks. Ethereum active addresses are now approaching levels not seen since January 2018. The following shows daily active addresses smoothed using a 7-day rolling average.

Source: Coin Metrics Network Data Pro

Market Data Insights

This past week in Bitcoin was relatively quiet, with daily volatility reaching the lowest levels in three months. This level of volatility was last seen the week of March 7th, 2020, just days prior to the roughly 50% drop in price on March 12th. Historically, Bitcoin has not been able to maintain volatility below the 50% threshold for periods of time. Is this time different or will volatility be returning soon?

Bitcoin’s rolling 30 day average volatility has only fallen below the 50% threshold 35 times during the modern Bitcoin market (if we consider the modern market for Bitcoin as starting when Bitcoin initially hit $1,000 on November 29, 2013).

Below is a histogram of the number of days that Bitcoin’s 30 Day volatility has remained below 50% for those 35 points mentioned above. 80% of those periods lasted less than 20 days, with 55% lasting less than 10 days. These percentages skew higher when looking only at data since 2017. To keep the following analysis more concise and relevant for the current trading regime we will continue to focus on just the period since 2017.

This leads us to consider what happens following these periods of low volatility. Below is a look at the 10 days preceding and 50 days following periods where the volatility has fallen below 50%. You can see the median and mean trends in red, showing that pattern of rising volatility following the tenth day.

Is this a bullish or bearish signal?  It is difficult to say with certainty using solely historical price data. However, we thought it would be interesting to repeat the analysis above looking at change in price instead of volatility. The results are mixed – sometimes price rises and sometimes it falls. The median and mean therefore both hover around 0% up to 40 days out.

CM Bletchley Indexes (CMBI) Insights

All of the CMBI and Bletchley Indexes experienced losses this week with the exception of the Bletchley 40 (market cap weighted and even weighted) which was up 1.1%. The CMBI Bitcoin Index and CMBI Ethereum Index were down 2.7% and 2% respectfully. 

Interestingly, the Bletchley 10 index, which is composed 82% of Bitcoin and Ethereum, was down 5.1% for the week, implying underperformance in the other constituent assets of the Bletchey 10 (XRP, XTZ, BCH, LINK, BSV, LTC, XLM, EOS). 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 54 – Analyzing Stablecoin Supply and Activity Distribution

Analyzing Stablecoin Supply and Activity Distribution 

By Antoine Le Calvez and the Coin Metrics Team

Key Takeaways

  • The supply and activity distribution of a stablecoin can help us understand how it is used. 
  • The ERC-20 variant of Tether shines as being particularly well distributed amongst its holders. Meanwhile, 6 accounts or less own 80+% of the supply for Gemini Dollar, Binance USD, Tether (Tron), USDK, and HUSD.
  • At first, Paxos appears to have a broad active user base. However, looking at the top transactors on Paxos leads to an interesting discovery: the two most active accounts on Paxos are linked to MMM BSC, a ponzi scheme which underwent an exponential growth in activity in the past year.
  • Another interesting discovery is that the most active Tether on Tron accounts are linked to “dividend” payouts. In some days, this was responsible for 90+% of Tether on Tron transfers.
  • Some stablecoins like Paxos and Tether on Tron see a lot of retail-like transactions, probably due to the presence of MMM and other dividend schemes on these assets. Other stablecoins like HUSD and Binance USD have a large share of payments above $100k.

Introduction

One of the biggest changes in the crypto industry over the past years has been the emergence and development of stablecoins. Split across many networks (Bitcoin, Ethereum, Tron and more) and issuers (Tether, Circle/Coinbase, Binance, etc.), these assets share many similarities: they have the same price, often use the same tech (ERC-20) and serve similar users.

In this piece, we will look at stablecoins network data and try to understand how their usage varies across the networks they are based on and their issuer. More particularly, we will look at Tether (on its Omni, Ethereum and Tron versions), Paxos, USDC, TrueUSD, Gemini Dollar, HUSD, Binance USD, and USDK.

Supply Distribution

The supply distribution of a stablecoin can help us understand how it is used. If it is only used on few exchanges without much other activity, most of the supply will be concentrated in few addresses. On the contrary, if it’s used by many exchanges and users, it will be more broadly distributed.

The ERC-20 variant of Tether shines as being particularly well distributed amongst its holders. Meanwhile, 6 accounts or less own 80+% of the supply for Gemini Dollar, Binance USD, Tether (Tron), USDK, and HUSD.

USDK has a particularly strange supply distribution. As of writing, 3355 accounts hold USDK, but 3170 (94%) only own either $0.5 or $1 which they received in July 2019 from an account who in turn got its money from OKex. Given that barely any recipient spent their money, it doesn’t look like a traditional airdrop.

Activity Distribution

Another way to compare stablecoins is to look at how many accounts are responsible for the majority of the on-chain activity (e.g. 80% of all on-chain activity, as in the chart below). If a small number of accounts are responsible for most of the transactions, it shows a lack of use outside of a handful of exchanges.

Note: For USDK, we exclude the activity related to crediting the 94% of accounts holding only $0.5 or $1.

At first, Paxos appears to have a broad active user base. However, looking at the top transactors on Paxos leads to an interesting discovery: the two most active accounts on Paxos are linked to MMM BSC, a ponzi scheme which underwent an exponential growth in activity in the past year.

Nowadays, more than 40% of all PAX transfers are directly related to this scheme.

Another interesting discovery is that the most active Tether on Tron accounts are linked to “dividend” payouts. In some days, this was responsible for 90+% of Tether on Tron transfers.

Continue Reading on the Coin Metrics Blog

Continue reading the full article on the Coin Metrics blog.

Network Data Insights

Summary Metrics

Ethereum continues to surge, with an 11% increase in both market cap and active addresses week-over-week. While Bitcoin’s market cap and realized cap also grew week-over-week, Ethereum once again led the way. 

Ethereum is also closing the gap in terms of daily transaction fees. Ethereum averaged $463.6K daily transaction fees over the last week, compared to $603.7K for Bitcoin.  Ethereum transaction fees rose towards the end of the week, and surpassed Bitcoin’s daily fees on both June 5th and 6th. We explore this trend more in today’s Network Highlights section. 

Network Highlights

On June 5th Ethereum had more total daily transaction fees than Bitcoin. While Ethereum also topped Bitcoin in terms of daily fees on March 12th (due to network congestion after the price crash), Bitcoin has had more daily fees than Ethereum for most of its history. 

After the recent halving, Bitcoin fees spiked to highs not seen since July, 2019. This rise in fees was mostly due to an increase in competition for block space, as explained in the Network Highlights section of State of the Network Issue 51.

But now Bitcoin fees appear to be dropping back to pre-halving levels. Bitcoin hash rate is recovering quickly following the halving, which means more blocks are being produced which leads to less block space congestion.

The following chart shows Bitcoin estimated hash rate, smoothed using a 7 day rolling average.

Simultaneously, Ethereum fees are spiking. This is at least in part due to the continued rise of Tether issued on Ethereum (USDT_ETH). USDT_ETH transfers surged to a new all-time high of 232.3K on June 6th.

In addition to hash rate, Bitcoin’s realized cap has recovered relatively quickly after the March 12th crash. Bitcoin’s realized cap reached $105.98B on June 6th and is approaching all-time highs. Bitcoin realized cap reached an all-time high of $106.26B in February 2020, before falling down to about $100B after March 12th.

Market Data Insights

To those following the digital asset space, few phrases can evoke as many feelings as “alt season.” Reading it here may stir up emotions of nostalgia, euphoria, greed and, of course, pain surrounding ‘the one that got away’.  

To those unfamiliar, alt season is the portion of the crypto currency investing cycle where the altcoins (smaller cap digital assets which are neither Bitcoin or Ethereum) are in favor. There is no strict definition, but you know it once it arrives. Common informal indicators include tokens with < $50m market caps going on multiple day runs of double-digit returns.  If you find yourself looking up tickers you read about in a forum, trying to predict the next Coinbase listing, or frustrated with how long it will take to transfer funds to an exchange listing your asset of choice, it might just be alt season.

In order to fully appreciate what happened in May, let’s put it in context with the trends in April.  April 2020 was a very positive month for the Bitcoin investment narrative. We had Paul Tudor Jones telling the world that Bitcoin was a sensible trade to hedge inflation risk. CARES Act stimulus checks went out which Coinbase data suggested led to a greater amount of deposits on their platform. Personal savings rates increased to 33% from 12.7% in March, leaving Americans with a larger cushion of cash to be allocated to crypto. Enough speculation though, let’s look at the data.

Notable in the April changes are the increases in Spot Volume Market share of Coinbase, Kraken and Bittrex. These exchanges are the typical fiat on-ramps for retail investors. 

In May, retail investors were feeling good. Bitcoin dip buyers aside, online stock brokers such as Robinhood, Fidelity, TD Ameritrade and E*Trade all reported record amounts of retail trader activity. This demographic of investors (read: speculators) who bought the dip on almost any heavily traded stocks benefited from a strong rally with the S&P 500 index gained 14% during the month of April.

A routinely studied trend in behavioral finance is that overconfident investors tend to move up the risk spectrum and take on more risk (one such study linked here). With this in mind, it is not surprising that we see the trend of trading volumes shifting from the fiat onramp exchanges to those servicing the long tail of riskier alt coins. 

Similar to what we looked at for April, the above chart shows the change in spot market share for selected exchanges in May. Notably Coinbase and Kraken, the fiat exchanges with increases in April saw declining market share in May. However, exchanges such as Binance and Okex saw large increases. These exchanges with increasing market share support trading for a longer tail of assets, i.e. altcoins.

To verify this shift in volume to said assets we take a look at the change in spot trading market share by base asset.

The visual above shows an asset’s share of spot volume at the beginning and end of May, measured using a rolling 7 day average up to and including the relevant date. Notice that there is a break in the chart’s x-axis between 3.5% and 10%. This allows us to better understand the share of volume represented while still including BTC and ETH for context.

We can see that during the month of May, the volumes for BTC and ETH both decreased, roughly by 5% and 2% respectively.  This share of volume shifted to assets such as ETC, OKb, Theta, OMG and MATIC.  Trading volume has moved into these riskier assets sending a strong signal that alt season has arrived.

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes had another strong week, with the multi-asset indexes performing the best. 

Both the CMBI Bitcoin Index and the CMBI Ethereum Index finished the week slightly up at 1.4% and 1.5% respectively. The Bletchley 20 (mid-cap assets) experienced the strongest returns, up 7.3% for the week, with the Bletchley 40 (small-cap assets) not far behind, returning 6.8%. 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 53 – Measuring Bitcoin’s Trading Volume

Measuring Bitcoin’s Trading Volume

by Kevin Lu and the Coin Metrics Team

Current market conditions have led to a resurgence of institutional interest in Bitcoin. In the face of an unparalleled monetary and fiscal policy response from central banks and governments around the world, more institutions are recognizing that such policies significantly increase the probability of policy error, either by inciting financial imbalances in certain sectors of the economy or by stoking higher levels of inflation. 

Here we examine, from the perspective of an institution considering entering the market, the distribution and size of Bitcoin’s volume across its various markets. The following is a preview of an upcoming research piece with ARK Invest which will feature a more comprehensive analysis of an institutional approach to Bitcoin.

The Many Facets of Bitcoin’s Volume 

Calculating Bitcoin’s market capitalization is relatively straightforward. Coin Metrics estimates Bitcoin’s free float market capitalization to be $136 billion, giving it a size similar to that of the largest publicly traded companies in the United States. An assessment of volume, however, is more complicated and different calculation methodologies can yield significantly different results. 

Bitcoin’s market structure is unique in that it most closely mirrors that of foreign exchange markets. It is similar in that it is globally distributed, operates 24 hours a day, and its markets utilize a base asset and quote asset convention. The exception is that a significant portion of trading volume occurs on centralized exchanges that match trades from any market participant rather than through an interbank market. 

Source: Coin Metrics Market Data Feed

Bitcoin’s daily trading volume can be evaluated at different levels of aggregation. For a buy-side institution interested in deploying fresh capital into the space, the trading volume of Bitcoin spot markets quoted in U.S. dollars of $0.5 billion per day from major exchanges is perhaps the most relevant. With this level of trading volume, a buy-side institution wishing to not exceed one percent of total trading volume could expect to deploy $5 million in capital per day. 

While the Bitcoin trading ecosystem consists of hundreds of centralized exchanges, a handful of decentralized exchanges, and several OTC desks, the majority of trading occurs on a set of major centralized exchanges. In this analysis, our volume figures are derived from a set of major exchanges consisting of Binance, Binance.US, Bitfinex, bitFlyer, Bithumb, BitMEX, Bitstamp, Bittrex, Bybit, CEX.IO, Coinbase, FTX, Gate.io, Gemini, Huobi, itBit, Kraken, Liquid, OKEX, Poloniex, and Upbit. 

Source: Coin Metrics Market Data Feed

Distribution of U.S. dollar quoted spot market volume follows a power law where roughly 90 percent of the volume is concentrated in the top four exchanges in our sample: Coinbase, Bitstamp, Bitfinex, and Kraken. The fragmented nature of trading volume and liquidity in this space indicates that institutions should expect to go through a process of onboarding with multiple exchanges to access the full spectrum of trading activity. 

Source: Coin Metrics Market Data Feed

Expanding the set of markets to include any fiat markets increases daily trading volume to $1.2 billion with the U.S. dollar consisting of roughly half of the total. Aside from the U.S. dollar, the major fiat quote currencies are the Japanese yen, the euro, the Korean won and the British pound. This set of major exchanges chosen in our analysis excludes some smaller regional exchanges, but their volume is too low to be realistically considered by institutions. 

Source: Coin Metrics Market Data Feed

Stablecoins have evolved to be systemically important to Bitcoin’s ecosystem and continue to gain trading volume market share. Including markets quoted in stablecoins significantly increases the daily trading volume to $3.5 billion, primarily due to Tether — a stablecoin which operates in a regulatory gray zone. Thus, buy-side and sell-side institutions must make a critical decision whether the advantages of participating in stablecoin markets in the form of increased liquidity and trading activity outweigh the risks. More regulatory compliant stablecoins such as USD Coin, Paxos Standard, or TrueUSD have insignificant volumes compared to Tether. 

Source: Coin Metrics Market Data Feed

The largest increase is observed when derivatives markets are added to the mix. Similar to other asset classes, derivatives markets in Bitcoin are several times larger compared to spot markets. If reported volumes are to be believed, gaining exposure through derivatives markets may be the most efficient path. However, crypto derivative markets are still developing, and market participants must contend with a confused mixture of differing contract specifications. Contracts that accept margin in and settle profit and loss in Bitcoin, stablecoins, and fiat all exist. 

Bitcoin’s Volume is Still Small But Growing

Assessing the many facets of Bitcoin’s trading volume can be aided with a frame of reference. Here we compare the spot volume of Bitcoin with the spot volume from other asset classes. 

Source: Coin Metrics Market Data Feed

With daily trading volume of only $4.1 billion, Bitcoin’s spot markets are still minuscule in comparison to U.S. equity markets, U.S. bond markets, and global foreign exchange markets. The interpretation is that Bitcoin, in its current state, is most comparable in size to a large capitalization stock rather than a distinct asset class. A large institutional investor such as an endowment, pension fund, or sovereign wealth fund might reasonably conclude that Bitcoin is only suitable for a portion of the already small allocation to alternative assets rather than carving out a separate allocation towards it. 

If historical growth rates can be maintained, however, Bitcoin’s current daily volume from spot markets of $4.3 billion would need fewer than 4 years of growth to exceed daily volume of all U.S. equities. Fewer than 5 years of growth are needed to exceed daily volume of all U.S. bonds. 

Source: Coin Metrics Market Data Feed

Conclusion

The fragmentation of trading volume in the Bitcoin ecosystem prevents a straightforward assessment of its market size. Institutions considering entering the space should first survey the landscape and make a determination of which exchanges, markets, and assets they feel comfortable transacting in. Critical decisions such as whether they would be willing to transact in stablecoins such as Tether or use derivatives such as perpetual futures contracts can have a material impact on evaluation of trading volume and liquidity. Regardless of these decisions, all facets of Bitcoin’s trading volume have experienced exponential growth and, if sustained, will grow to levels similar to major asset classes. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Ethereum (ETH) surged over the weekend and finished the week in the green for most metrics.  ETH daily transaction fees grew 11.0% week-over-week, with an average of $441.8K worth of fees per day. In contrast, Bitcoin (BTC) fees fell 48.6% week-over-week, after showing strong growth over most of May. BTC fees reached $1.82M on May 21st, which is the highest daily total since June 2019.

Network Highlights

When a transaction is broadcast into the Bitcoin network, before it can be included in a block it is temporarily held in a waiting area called the mempool (short for “memory pool”). Miners usually select the highest feerate transactions from the mempool to include in their mined block. 

After the halving, the Bitcoin mempool started filling up with transactions. This was a result of the hash rate drop and subsequent rise of the average interval between Bitcoin blocks following the halving, as reported in the Network Highlights section of SOTN Issue 51. A longer interval between blocks means fewer blocks being mined per day, which in turn results in fewer transactions confirming, causing the mempool to fill up. 

Over the last weeks, the Bitcoin mempool grew and peaked at about 80k unconfirmed transactions.

With the increased transaction count, two methods that Bitcoin Core software utilizes to self-regulate the mempool size could be observed. Firstly, transactions paying a low feerate of just above 1 sat/vByte were evicted from the mempool to make room for higher feerate transactions. The transactions kept in a Bitcoin Core node’s mempool are capped to only use a fixed part of the system’s memory.

In total 7,126 transactions were evicted between May 20th, 09:50 UTC, and May 22nd, 14:30 UTC. The evictions all happened during European and US business hours, the time with the highest network activity.

Secondly, transactions residing in the mempool for over two weeks expired. By default, Bitcoin Core nodes remove transactions from their mempool if no miner found transaction fees to be attractive enough to include them in a block over the last 336 hours (two weeks).

In total 1,627 transactions expired between May 25th, and May 30th. Only 35% of these resided in the mempool for two weeks. The remaining 65% likely spent unconfirmed parent transactions and became invalid as their parents expired.

Market Data Insights

Bitcoin Correlation With Gold Remains High 

The overall market environment continues to be favorable for Bitcoin. On the margin, the policy response to the coronavirus, the protest-related civil unrest in the United States, and the potential for a re-escalation of the trade war between the United States and China should be supportive for store-of-value assets such as Bitcoin. The correlation between gold has consistently maintained relatively high levels for several months now, a phenomenon that has not been historically observed. 

Source: Coin Metrics Reference Rates

Signs of Altcoin Season Regime Shift 

Some interesting signs are emerging that may mark the beginning of an altcoin season regime shift. Ethereum, the primary platform that the majority of altcoins are based on, has begun to outperform other major assets. Cardano is up over 40% this week after announcing a release date for its next major upgrade, named Shelley. And OmiseGo surged over 100% after Coinbase announced that it would begin listing the asset on its platform. Such market movements in response to mainnet launches, new product upgrades, and exchange listings are reminiscent of late 2017. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

In the last week of May, most CMBI and Bletchley Indexes recovered the previous week’s losses, with the CMBI Ethereum Index being the outstanding performer. Having only fallen 1% last week, the CMBI Ethereum Index was again the strongest performer, returning 14.7% this week.

All of the Bletchley Indexes experienced returns between 9% and 11%, demonstrating the uniform strength of the market across all large, mid and small cap assets.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 52 – Best of the First Year of State of the Network

Best of the First Year of State of the Network

By Nate Maddrey and the Coin Metrics Team

In this special edition, we look back at the best issues of the past year to celebrate State of the Network’s one-year anniversary. 

Over the last 52 issues we have taken a data-driven approach to elucidating the best (and worst) of crypto, powered by Coin Metrics’ network and market data. In this issue we look back at three specific themes that we have covered over multiple issues over the past year: 

  1. Transparency and auditability
  2. Valuation and market analysis
  3. Network security and health

We would also like to use this opportunity to wish a big thank you to everyone who has viewed and subscribed to State of the Network over the past year. Please let us know if you have any feedback about State of the Network, especially if you have ideas about how we can keep making it even better. You can submit feedback here

Transparency and Auditability 

At Coin Metrics, transparency and auditability are the foundational building blocks that our data and analysis are built on top of. This starts with running our own nodes for the cryptoassets we cover.

In Issue 30, we ranked full nodes in several tiers (A, B, C, and F) depending on their ease of synchronization, updatability, and maintenance. Below is our ranking for the top 10 assets by market cap (Coin Metrics doesn’t operate Ripple or Stellar nodes, but relies on the APIs provided by both Ripple and the Stellar Foundation).

Source: State of the Network Issue 30

Running our own nodes also allows us to audit supply, and trace which addresses supply flows through. In Issue 32 we investigated the Stellar inflation experiment and found that about 98% of Stellar inflation payments accrued to the Stellar Development Foundation (SDF).

Source: State of the Network Issue 32

In Issue 26 we did a deep investigation into the nuances of Bitcoin’s supply to determine how many Bitcoins are permanently lost. From those estimates of lost coins, we constructed adjusted views of Bitcoin’s supply.

Source: State of the Network Issue 26

This supply investigation eventually led us to the introduction of CM Free Float Supply in Issue 48, a new metric that is being developed to more accurately represent the supply of an asset available to the market.

Source: State of the Network Issue 48

Accurate supply measurements have also played a foundational role in our research into cryptoasset usage patterns. In Issue 38 we analyzed the supply distribution of eight cryptoassets. We found that Bitcoin and Ethereum were gradually getting more distributed, while BCH and BSV were not. 

Source: State of the Network Issue 38

Over the year, we also followed the rapid rise of both the supply and market capitalization of Tether and other stablecoins. Total stablecoin market cap grew from about $4.35B at the beginning of June 2019 to over $10B as of May 2020. We covered the rise of stablecoins in Issue 15Issue 17Issue 25Issue 38Issue 47, and more.

Source: State of the Network Issue 47

Valuation and Market Analysis 

Over the past year we also devoted a lot of time to valuation research and market analysis. 

In Issue 37, we released the first part of our “Cryptoasset Valuation Research Primer.” In Part 1 we explored six main categories of crypto valuation research: equation of exchange, discounted future utilities model, Metcalfe’s law, price regression models, cost of production models, and asset bubble identification. 

In Part 2 of our cryptoasset valuation primer in Issue 40, we surveyed five additional facets of the literature: fundamental ratios, UTXO age analysis, realized capitalization-based analysis, factor investing, and social media-based analysis. We followed this up with a deep-dive into a specific fundamental ratio, Market Value to Realized Value, in Issue 41.

Source: state of the Network Issue 41

We also analyzed extreme market movements, both positive and negative. In Issue 19, after Bitcoin experienced its largest single-day decline in price in 2019 to date, we used on-chain data to show that selling pressure originated from traders that acquired Bitcoin at prices between $10,000 and $12,000.

Source: State of the Network Issue 19

In Issue 23, after Bitcoin bounced back and experienced one of the largest 24-hour returns in its history (at the time), we analyzed our trades data, which is part of our Market Data Feed offering, and found that spreads between major exchanges remained small, indicating that market participants have the ability to quickly transport liquidity across markets. 

Source: State of the Network Issue 23

In Issue 42, after the March 12th 2020 crash, we again looked at the spread between exchanges and observed a large spread of around 16% between BitMEX and Coinbase during the sell-off. This was likely due to the BitMEX liquidation spiral after BitMEX went down for unscheduled maintenance in the early hours of March 13th, which we covered in detail in Issue 43.

Source: State of the Network Issue 42

We also used our realtime reference rates to track how Bitcoin reacted to geopolitical and macroeconomic events in real-time. In Issue 33, we analyzed Bitcoin’s response to growing military tensions in Iran.

And in Issue 12, published on August 13th, 2019, we began to analyze the theory that Bitcoin acts as a unique safe haven asset. We revisited the safe haven theory in Issue 33Issue 39Issue 45.

In Issue 46, we conducted a correlation analysis using our reference rates and intraday equity data, and found that while there are pieces of evidence that the correlation between Bitcoin and gold may be growing, Bitcoin’s overall correlation with gold is still relatively weak.

Source: State of the Network Issue 46

Network Security and Health

Security and mining analysis has been another theme for State of the Network over the last year. To assess the long-term health and security of a crypto network, it’s critical to track different security metrics like hash rate and miner rewards. It’s also crucial to keep track of hashpower distribution, both among different entities and among different types of mining hardware.

In Issue 23, we started exploring a novel technique of analyzing nonce distributions to find evidence of specialized types of mining hardware called ASICs.

We continued this line of research in Issue 45, where we extended the nonce analysis to identify different mining pools and estimate the usage of specific types of hardware.

Source: State of the Network Issue 45

We revisited the nonce distribution research once again in Issue 51, after Bitcoin’s third halving on May 11th, 2020. Using our techniques for estimating the types of mining hardware being used, we estimated that a significant number of formerly-offline S9s were turned back on prior to the halving. While the amount of hashpower that could be created by offline S9s is nowhere near enough to 51% attack the network, the change to the network’s security dynamics caused by their presence is significant.

Source: State of the Network Issue 51

We also analyzed prior halvings by looking back at historical data. In Issue 44, using a set of axioms, we provided a framework reasoned from first principles that illustrates how miners are a continuous and significant source of selling pressure that has a pro-cyclical impact on prices.

Source: State of the Network Issue 44

Our research on security also led us to designing improved ways to measure it. In Issue 49, we introduced the CMBI Bitcoin Index and ‘Observed Work’ as a more reactive, responsive and manipulation resistant way to measure the realities of mining activity when compared to traditional hash rate estimations. 

Additionally, Observed Work and Coin Metrics’ CMBI Bitcoin Hash Rate Index can potentially serve as the foundational pieces of financial products that can provide markets with the required tools to effectively and efficiently trade and/or hedge Bitcoin’s hash rate.

Source: State of the Network Issue 49

Conclusion 

It has been a great year of data-driven analysis focused on transparency and auditability, valuation and market analysis, security analysis, and much more. Thanks again for your readership, and please leave us feedback if you have any ideas or comments. We look forward to continuing to bring you the best data-driven crypto stories for years to come.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • This has been a special edition of State of the Network. The regular format including Network Data and Market Data section will return next week.
  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 51 – The Half-Time Show: The State of Bitcoin Network Security After the Halving

The Half-Time Show: The State of Bitcoin Network Security After the Halving

By Karim Helmy and the Coin Metrics Team

Key Takeaways

  • Block rewards are currently the primary source of revenue for miners. A reduction in this reward due to the halving causes some miners to exit the network. In the short term the sudden drop-off of miners can potentially leave the network more exposed to security threats like 51% attacks. 
  • The distribution of hashpower among different types of mining hardware also has an impact on the network’s security properties. The availability of old hardware on secondary markets poses a potential threat to the network.
  • Novel techniques involving nonce distributions allow us to numerically estimate the amount of hashpower provided by certain types of hardware, including older hardware like S7s and S9s.
  • It now appears that a significant number of formerly-offline S9s have been turned back on. Currently, the Antminer S9 family of miners is responsible for about 32% of Bitcoin’s hashpower.
  • While the amount of hashpower that could be created by offline S9s is nowhere near enough to 51% attack the network, the change to the network’s security dynamics caused by their presence is significant.

Halving a Good Time

On May 11th, for the third time in Bitcoin’s history, the amount of new coins issued per block was cut in half. This event, known as the halving, occurs every 210,000 blocks, or approximately four years, until issuance is eventually rounded down to zero.

In the most recent halving, the block reward was reduced from 12.5 to 6.25 BTC. The period leading up to the halving was marked by pronounced market volatility, which has somewhat subsided since the reduction occurred. The impacts of the event on the network’s security are nuanced.

Block rewards are currently the primary source of revenue for miners, so a reduction in this reward causes some miners to exit the network. With less revenue to go around, margins are tightened and less efficient miners may suddenly find themselves operating at a loss. In the long run, these miners are typically replaced by more efficient operations as the market rebalances. In the short term, however, the sudden drop-off of miners can leave the network more exposed to security threats like 51% attacks. 

State of the Network Issue 44 reasoned about the impacts of the halving on miner economics from first principles. This piece will address a similar topic, focusing on the implications of the halving on security and the economics of running old mining hardware. In the process, we’ll use nonce data to estimate the prevalence of certain types of hardware on the network today, and discuss how the presence of old hardware impacts Bitcoin’s security model.

To Halve and to Secure

Bitcoin miners are compensated through both block rewards, which are directly affected by the halving, and transaction fees, which are not. Transaction fees are generally a function of demand for block space, and therefore tend to spike during periods of congestion and high traffic. 

Currently, fees make up a small percentage of total miner revenue. Over the past five years, only about 4.4% of miner revenue has been generated from fees.

Source: Coin Metrics Network Data Pro

As Bitcoin’s block reward continues to halve approximately every four years, transaction fees will need to increase in order to sufficiently incentivize miners to secure the chain. Since slightly before the halving, fees have surged to make up about 17% of total miner revenue. While this effect has been intensified by the reduction in the block reward, transaction fees themselves have also increased to levels not seen in almost a year.

This increase in fees may have been amplified by the reduction in hash rate that has taken place since the halving. This reduction, in turn, is caused by less efficient miners leaving the network. The drop in hashpower has increased the time between blocks, therefore reducing the amount of available block space.

To reduce the variance of their payouts, miners often aggregate into mining pools, which are loose coalitions of miners that are organized by an operator and share revenue, typically according to hashpower contribution. Individual miners often switch between pools depending on several factors, most notably fees charged by operators.

As long as no single dishonest entity controls more than half of Bitcoin’s hashpower, the network is secure. In a process known as a 51% attack, an adversary who controls more than half the network’s hashpower can censor transactions and perform double-spends.

The minimum number of pools who would need to collude in order to 51% attack the network is known as the Nakamoto coefficient. At this time, the top 4 pools would need to collude in order to 51% attack the network. This number has generally gone up over the course of Bitcoin’s history, indicating a steady increase in decentralization.

The Nakamoto coefficient is not a perfect metric, and makes Bitcoin seem significantly more centralized than it is. Individual miners, who face large up-front expenses on capital like hardware, are disincentivized from attacking the network. These miners would likely defect from a maliciously-operated pool.

Still, pools select the blocks that their constituents mine, and barring defection exercise a certain degree of control over them. It also may be possible for an attacker to censor transactions with less than half of the network’s hashpower through techniques like feather-forking. It’s therefore useful to have a pessimistic metric like the Nakamoto coefficient to quantify the degree of centralization among miners.

Stratum V2, an implementation of Betterhash with modifications to the original protocol, suggests letting individual miners select the blocks that they will mine, rather than the pool operators doing so. This potential improvement to the way pools are operated would put more power in the hands of individual miners, further decentralizing the network. 

In addition to the distribution of hashpower among different entities, the distribution of hashpower among different types of mining hardware has a significant impact on the network’s security properties.

Hardening Hardware

To add a block to the blockchain, Bitcoin miners attempt to find a nonce, or arbitrary value, that causes the block header to hash to below a certain target. The rate at which these hashes are computed and verified is known as hashpower, and a nonce satisfying this condition is called a golden nonce. Golden nonces are theoretically uniformly distributed throughout the space of potential nonces and valid blocks. The threshold that the hash of the block header must satisfy is set by the network’s difficulty parameter, which is periodically adjusted according to the rate at which blocks have been accepted to the chain. 

While mining was initially performed with CPUs, the process was parallelized and made more efficient early-on through the adoption of GPUs. Today, almost all mining is performed using mining rigs that contain specialized chips known as ASICS. These devices are significantly faster, better at parallelization, and more energy-efficient than other hardware.

Purchasing these devices requires a large up-front capital expenditure. This benefits the security of the network by requiring miners to lock up capital in an illiquid asset and therefore disincentivizing them from acting maliciously.

The presence of old mining hardware changes this security model, since it tends to require smaller up-front investment at the expense of higher operating costs. While there are practical and logistical barriers to starting a mining farm aside from the cost of hardware, the presence of old hardware allows entry into the market with significantly reduced capital expenditure.

Due to secrecy in the mining industry, it’s generally difficult to discern which types of mining hardware are being used to secure the network. However, novel techniques allow us to numerically estimate the amount of hashpower provided by certain types of hardware. 

Bitcoin’s nonce distribution offers hints at the types of hardware being used to mine on the network. By combining this data with information on the prices of hardware on secondary markets, we can quantify the degree of risk posed by the existence of inexpensive, slightly dated hardware. For a detailed explanation of our analysis of nonce distributions, see our series “The Signal and the Nonce” Part 1 and Part 2.

Since golden nonces are uniformly distributed throughout the nonce spaces of all potential blocks, we’d expect a plot of the winning nonces over time to look like random static. Bitcoin’s nonce distribution doesn’t.

Near the left-hand side of the plot, nonces are concentrated in the lower ranges of the distribution. This is a result of a sampling technique used by miners in the CPU-mining era, which involved iteratively testing values starting from zero and incrementing upward.

Bitcoin’s nonce distribution also has a characteristic streaked pattern that first appeared in late 2015, and has recently begun to fade. The striations in question start out broad, and then suddenly narrow out, before gradually fading away. There are four distinct streaks, each of which can be specified in terms of its narrow and wide bands.

These streaks were noted in State of the Network Issue 23, and their source was identified in State of the Network Issue 45. The striations were found to come from the way in which nonces are sampled by the Bitmain Antminer S7 and S9 mining rig lines. Each of these rigs was at one point the dominant miner on the network, with the S9 having recently been supplanted in this role by the Antminer S17.

The wide and narrow bands are attributable to the sampling techniques used by the S7 and S9 families, respectively. We can use this knowledge to numerically estimate the proportion of the network’s hashpower provided by S7s and S9s.

According to these numerical estimates, the proportion of hash rate provided by S7s and related hardware peaked in May of 2016 at about 61%. Today, S7s are not responsible for a significant portion of hashpower. The proportion of blocks mined by S9s and related hardware peaked in May of 2018 at about 78%. Today, about 32% of blocks are produced by S9s. 

These estimates are based on the assumption that S7s and S9s do not sample within their respective excluded bands and that all miners sample uniformly outside of any excluded regions. These conditions are violated in the CPU-mining era, but appear to hold from the GPU-mining period onward. The excluded regions are determined manually, and estimates are corrected for any extrapolated values outside of the 0-100% range and normalized.

The estimates are subject to a certain amount of noise, which is visible toward the left of the graph. The small bump in the estimated proportion of S9 hashpower in 2015 could be due to noise, or may be a sign of something else such as the testing of experimental hardware.

These figures are consistent with other estimates of the hashpower output of these types of hardware. A CoinShares report on Bitcoin mining released in December 2019 estimated that S9s made up about two thirds of the hardware in their equivalence class. In March, the founder of Beijing-based Spark Capital estimated that S9s provided 20 to 25 percent of Bitcoin’s hashpower.

The proportion of hashpower provided by each type of mining rig provides further perspective on the threat posed by old hardware.

The most salient insight from this plot is the exponential growth in the hashpower securing the network.

The estimated amount of hashpower provided by S9s reached its peak in August of 2019, when they generated about 52 exahashes per second. In February of 2020, the estimated hashpower generated by S9s reached the bottom of a valley at about 21 exahashes per second.

It now appears that a significant number of formerly-offline S9s have been turned back on, likely as a result of a recent appreciation in the price of Bitcoin. This hardware now computes about 37 exahashes per second.

Due to rapidly changing market conditions, this effect may not be sustained. However, it illustrates the degree to which mining with old hardware may be viable given favorable conditions, and the ease with which this less-expensive hardware can be deployed.

S9s are being sold on secondary markets for a fraction of their retail price. The miners can be purchased for between $20 and $80, compared to an original price of about $3000. Given today’s economic climate and the inexpensive electricity brought on by China’s rainy season, miners have found it possible to operate these devices profitably.

While the amount of hashpower that could be created by offline S9s is nowhere near enough to 51% attack Bitcoin, the change to the network’s security dynamics caused by their presence is significant. This effect may be felt more acutely by other platforms that use Bitcoin’s proof of work algorithm, including Bitcoin Cash and Bitcoin SV, which are currently secured by about 2.5 and 1.8 exahashes per second of computational power, respectively.

The Epitaph of the Third Epoch

In anticipation of the halving and on optimism related to increased institutional interest, the price of Bitcoin increased dramatically before giving up some of its gains. Since the halving, volatility has subsided somewhat, but price has continued to trend upward. The halving has also accelerated an increase in transaction fees and precipitated a slight drop in hashpower.

Halving-related sentiment will continue to impact the market, and the halving itself will continue the test of whether Bitcoin can successfully transition to a model where miners’ revenue is predominantly based on fees. The long-term effects of this event remain to be seen, but its impact on the economics of mining and the market as a whole are already pronounced.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) and Ethereum (ETH) transaction fees continue to climb, despite a relatively flat week for most other metrics. 

Bitcoin’s median transaction fee reached $2.88 on May 14th, its highest level since June 2019. Similarly, Ethereum’s median transaction fee reached $0.25 on May 14th, its highest level since August 2018. Median transaction fees tend to surge when blocks are relatively full. The causes for this surge are explored in today’s Network Highlights section.

Network Highlights

Bitcoin’s hash rate has dropped to 81.66 TH/s following the halving, about a 40% drop from pre-halving highs. As noted in this week’s Weekly Feature, this hash rate drop-off is to be expected as less efficient miners exit the network. It will likely recover after a period of churn where efficient miners replace less efficient operations. However, it is unclear exactly how long this turnover period will last.

Source: Coin Metrics Network Data Pro

As a result of the hash rate drop, the average interval between Bitcoin blocks has risen to its highest levels since late 2018 (excluding the period around March 12th 2020, where block interval shot up due to the sudden drop in Bitcoin price and subsequent hash rate drop-off). 

Since there are less blocks being produced there is more competition for block space, which has led to the increase in transaction fees. Paying a higher transaction fee leads to a higher chance that miners will include the transaction in a block. So median fees tend to surge during periods where block space is at a premium.

Source: Coin Metrics Network Data Pro

The decrease in the overall number of blocks has also led to an increase in the size of each individual block. Bitcoin mean block size reached a new all-time high of 1.32 MB on May 17th.

Ethereum median transaction fees have also shown signs of growth since the Bitcoin halving. However, Bitcoin Cash (BCH), Bitcoin SV (BSV), Ripple (XRP), and Litecoin (LTC) median fees have not shown any significant increases.

Source: Coin Metrics Network Data Pro

Market Data Insights

This marks the third consecutive week that Bitcoin has outperformed other cryptoassets and forms a trend that cannot be ignored. Although it cannot be ruled out that this trend is simply a byproduct of the random walk of prices, one plausible explanation is that Bitcoin’s store of value properties are increasingly needed in today’s market environment. And as we observe the emergence of adoption by institutional investors, Bitcoin is the logical first choice as the gateway asset that may lead to the eventual adoption of cryptoassets as a distinct asset class. 

Source: Coin Metrics Reference Rates

A Call Option on Inflation 

There is an emerging narrative that Bitcoin is needed in a market environment of unparalleled monetary and fiscal policy by global central banks and governments. To examine this phenomenon, we show the year-over-year change in the Fed’s balance sheet highlighting the speed and magnitude of the Fed’s reaction to COVID-19. The Fed’s policy response has already exceeded the balance sheet expansions seen in the three previous quantitative easing programs following the financial crisis. 

Bitcoin’s strong returns lately and the renewed interest in Bitcoin as a store of value in a rising inflation environment is remarkable because all indicators are still showing that inflation is not a problem, despite the strong growth in money and credit. 

The shutdown of large swathes of the economy represents a demand shock which is deflationary by nature — energy prices reaching unprecedented lows are a prime example. Although monetary and fiscal policies are effective at getting money into the hands of U.S. businesses and households, the velocity of money has simultaneously declined. The most recent print for the U.S’s core inflation, which excludes food and energy items, fell 0.4% over the previous month, the largest monthly decline in the history of the series, according to the Bureau of Labor Statistics. 

Similarly, inflation expectations either from survey-based indicators, such as the University of Michigan’s Survey of Consumers, or market-based indicators, such as 5-year, 5-year forward inflation expectations derived from TIPS, are well-anchored. 

How can we reconcile the fear that Bitcoin will be needed in a rising inflation environment with the data that shows that realized inflation in the short-term is non-existent and inflation expectations over the medium to long-term are low? According to the Fed’s Survey of Consumer Expectations, median expectations for inflation have not meaningfully changed in response to the pandemic, but the level of uncertainty and disagreement across respondents have seen unprecedented increases

One framework to bring clarity to this question is to view Bitcoin as a call option on inflation and to examine its greeks: the sensitivities of the price of the option based on the parameters of the underlying. What we are seeing now is an increase in the implied volatility of future inflation even if median expectations for the future level of inflation remain unchanged. 

Standard option price theory indicates that increases in implied volatility of the underlying should lead to an increase in the price of a call option. Therefore, we can potentially attribute the recent increase in price of Bitcoin to the increase in implied volatility of inflation rather than the increase in the expected level of inflation. 

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes had very good weeks, ending between 5% and 15% higher than the previous week’s close. Following the biggest news of the week, the Bitcoin Halving, the CMBI Bitcoin Index was the strongest performer, returning 14.4%. The CMBI Ethereum Index also had a strong week, closing 11.9% higher. Despite these two strong performances though, it was the Bletchley 40, small-caps, that was the best of the market cap weighted indexes, closing the week 12.1% up.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 50 – Stablecoin Heatmaps Show Tether is Mostly Used During Asian and European Market Hours

Stablecoin Heatmaps Show Tether is Mostly Used During Asian and European Market Hours

by Nate Maddrey and the Coin Metrics Team

Key Takeaways 

  • Stablecoin market capitalization has almost doubled since the Black Thursday crash. But the exact cause of the surge is still unknown. 
  • To help elucidate how different stablecoins are being used, we analyzed the times of day that stablecoins are being transferred and created heatmaps to show daily usage patterns.
  • USDT-ETH has a clear pattern of heavy usage from about 2:00 to 16:00 UTC which corresponds with the hours that Asian and European stock markets are open.
  • Prior to March 12th PAX transfers appear to also mostly be clustered between 2:00 and 16:00 UTC (although not as dense as USDT-ETH). But as of April, PAX transfers have gotten noticeably more dispersed throughout the day. 
  • Prior to March 12th USDC was slightly denser during U.S. hours. But after March 12th there has been a large uptick in usage between 1:00 and 8:00 UTC, which corresponds with Asian market hours. 
  • DAI transfers have mostly been concentrated during U.S. working hours (14:00 – 22:00). 

Intro

Stablecoin market capitalization has almost doubled since the Black Thursday crash, despite a drop-off for most non-stablecoin assets. As of May 7th, the aggregate stablecoin market cap has grown to over $10B.

Source: Coin Metrics Community Data

There have been many theories about what has been causing this dramatic increase. 

Some have speculated that the growth is caused by an increase in the amount of investors holding stablecoins as “dry powder” in anticipation of a new bull run. Others have proposed that it’s a reaction to a shortage of U.S. dollars, or a general rush to safety. Another theory is that Asian OTC traders are pouring money into stablecoins as an onramp to crypto markets. 

While the exact cause of the market cap increase is still unknown, on-chain data can help point us in the right direction. In this week’s State of the Network we dive into on-chain transfer data to analyze the usage patterns of different stablecoins in order to shed light on some of the different theories about why market cap is growing.

Stablecoin Transfer Heatmaps

To help elucidate stablecoin usage patterns, we broke down stablecoin transfers by time of day. 

The following heatmaps show the amount of stablecoin transfers by hour of day for different Ethereum-based stablecoins. The x-axis is the date, starting from the beginning of February. The y-axis is the hour of day ranging from 0 – 23 (UTC time zone). And the coloring represents the amount of transfers that occurred during that one hour block. So for example, the cross-section of March 1st on the x-axis and 0 on the y-axis represents the amount of transfers that occurred from 12:00 – 1:00 AM on March 1st.

Tether

We start by investigating the transfer patterns of Tether issued on Ethereum (USDT-ETH). 

USDT-ETH has a clear pattern of heavy usage from about 2:00 to 16:00 UTC which corresponds with the hours that Asian and European stock markets are open. Transfers go dark towards the end of the day – there are very few transfers after 20:00, which is when the New York Stock Exchange closes.

The amount of transfers has also grown significantly since the middle of March. There are clusters of red (i.e. high transfer counts) towards the end of April, which appears to correspond with the hours that Asian markets are open. 

While the above heatmap shows the total number of transfers per hour, the following heatmap shows the percentage of the total daily transfers that happened within that hour.

For example, if there were 100,000 daily USDT_ETH transfers and 6,000 happened between 8:00 and 9:00 UTC that hour would account for 6% of the daily total and would be colored yellow/orange. This gives a slightly clearer picture of daily usage patterns, regardless of the total number of transfers.

The following heatmap also shows that USDT-ETH is mostly transferred during Asian and European hours, with a flurry of activity towards the close of Asian markets. This bolsters the theory that USDT-ETH is being used by Asian traders.

Paxos

Paxos (PAX) usage has also increased dramatically since March 12th. In fact, PAX daily transfers have tripled since March 12th, and reached a new all-time high of 24.4K on May 5th.

As a result, PAX has passed both USDC and DAI in terms of daily transfer count.

Prior to March 12th PAX transfers appear to also mostly be clustered between 2:00 and 16:00 UTC (although not as dense as USDT-ETH). 

But as of April, PAX transfers have gotten noticeably more dispersed throughout the day. The on-chain transfer data potentially shows that PAX is increasingly getting non-institutional, global usage.

USD Coin

USD Coin (USDC) had a huge amount of activity on March 12th and the following week, but has dropped off since then. Notably, MakerDAO added USDC as a collateral option on March 17th, which likely contributed to the flurry of transfers.

Prior to March 12th USDC activity was slightly denser during U.S. hours.  But after March 12th there has been a huge uptick in usage between 1:00 and 8:00 UTC, which corresponds with Asian market hours. 

Interestingly, USDC had a string of days in April where close to 20% of daily transfers occurred in a single hour. The other stablecoins in our study did not have over 12% of daily transfers in a single hour.

DAI

Similar to USDC, DAI had a large increase in transfers on March 12th and the days immediately following, but has dropped off since then.

DAI transfers have mostly been concentrated during U.S. working hours (14:00 – 22:00). However DAI transfers are relatively spread out, and not nearly as concentrated as USDT-ETH.

Conclusion

Stablecoin transfer patterns show that different stablecoins are potentially being used for different purposes, and are favored in different parts of the world.

USDT-ETH transfers are concentrated during Asian and European market hours. USDC transfers are also clustered during Asian market hours, but not as densely packed as USDT-ETH. PAX transfers are more dispersed, which could signal that it is being used for non-institutional purposes. And DAI transfers mostly occur during U.S. hours.

Stablecoins are a crucial part of the crypto ecosystem, and will only keep growing in prominence. We will continue to keep our eye on stablecoins, and track their usage and growth as they continues to develop. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Both Bitcoin (BTC) and Ethereum (ETH) had another mostly strong week in the lead up to BTC’s halving. BTC’s market cap briefly topped $180B as price approached $10,000. The week ended on a volatile note, however, with BTC market cap dropping back down to about $160B. 

BTC and ETH transaction fees were both up over 30% again this week, after ETH fees grew by 31% last week and BTC fees grew by a massive 170%. Fee growth is a positive sign that demand for block space is growing, which generally signals that network usage is increasing.

Network Highlights

BTC hash rate grew to all-time highs in the lead up to the halving. As the halving approached, miners rushed to get the last of the 12.5 BTC reward blocks, causing hash rate to increase and average block time to decrease. 

The following chart shows BTC hash rate smoothed using a seven day rolling average.

Source: Coin Metrics Network Data Pro

The amount of BTC held by BitMEX and Bitfinex has reached new lows following the March 12th crash. Bitfinex now holds 93.8K BTC, down from 193.9k on March 13th. BitMEX’s BTC supply is now down to 216.0K BTC, down from a peak of 315.7K on March 13th.

Source: Coin Metrics Network Data Pro

Meanwhile, the amount of ETH held on Bitfinex continues to climb to new highs. As of March 10th, Bitfinex held over 5M ETH. 

Source: Coin Metrics Network Data Pro

Market Data Insights

The most noteworthy market news this week was the endorsement of Bitcoin by hedge fund manager Paul Tudor Jones. In a note shared to clients, he cites its attractive store of value characteristics in the face of unparalleled monetary stimulus that he has termed the “Great Monetary Inflation”. 

Markets had a rational response to the news with Bitcoin outperforming most other major cryptoassets. This marks the second consecutive week of notable outperformance and deserves continued observation. 

For nearly a year, correlation between Bitcoin and other assets has remained high and dispersions in returns has remained small, but history has shown us that these periods of calm are interspersed with periods of large shifts within crypto markets. In our previous State of the Networks, we have commented on these regime shifts and the difficulty it poses for fund managers. 

The somewhat moderate reaction and the lack of large moves in traditionally high-beta altcoins suggests that we are still far from the irrational investor sentiment that characterizes the late stage of market bubbles. 

Source: Coin Metrics Reference Rates

Paul Tudor Jones’s prediction of unchecked monetary stimulus leading to an increase in inflation is still, surprisingly, a contrarian view that is not yet priced in according to five-year, five-year forward inflation expectations. This measure of inflation is widely cited as a proxy for long-term inflation expectations that is less sensitive to the demand shocks of today or the volatility of food and energy prices. 

So far, despite everything that has happened, inflation expectations are stable and the Fed still has its credibility intact. In short, the market believes that the Fed will do what is necessary to defend its price stability mandate. The issue is that we could face a situation where the Fed’s dual mandate of maximum employment and price stability becomes untenable and it will have to favor one over the other. These fears manifested itself in higher inflation expectations in the years following the 2008 financial crisis leading to a multi-year period where assets that rose from rising inflation expectations benefited. Ultimately, the inflation alarmists were proven incorrect as the Fed was able to thread the needle and provide enough stimulus to heal the economy without stoking undue inflation.

The market is betting that it will do the same this time. But it is clear that if the market is incorrect, we could see much higher prices for Bitcoin in the future. 

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes gave up most of last week’s returns, except for the Bletchley 40 and Bletchley 40 Even which were the only indexes that finished the week positive, returning 4.6% and 5.1% respectively. Whilst the CMBI Bitcoin Index was down 3.9%, it was the CMBI Ethereum Index that retraced the most during the week, falling 11.1%. 

Even weight indexes are a mechanism of gaining greater exposure to the smaller-cap assets and as such, can often provide different return profiles to market cap weighted indexes. This week’s return profile demonstrates just that, with even weighted indexes, excluding the Bletchley 10, outperforming their market cap weighted counterparts for the week. This type of performance demonstrates that the lower weighted assets within each index were some of the better performers. 

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 49 – Introducing the CMBI Bitcoin Hash Rate Index and ‘Observed Work’

Designing The Tools For Hash Rate Futures: Introducing the CMBI Bitcoin Hash Rate Index and ‘Observed Work’

By Ben Celermajer and the Coin Metrics Team

Key Takeaways

  • To date, the critical role of Bitcoin miners has been unhedged and solely dependent on the price of Bitcoin. However, as the mining market continues to mature with the inclusion of traditional market participants, these companies will seek mechanisms to hedge their exposure and operations much like they do with other traditional assets.
  • The current way of estimating hash rate, which involves a calculation process that includes a set lookback period (e.g. 48 hours), makes it difficult to design financial products that could help miners hedge their risk.
  • Coin Metrics has designed the CMBI Bitcoin Index and ‘Observed Work’ as a more reactive, responsive and manipulation resistant way to measure the realities of mining activity when compared to traditional hash rate estimations. 
  • Observed Work and Coin Metrics’ CMBI Bitcoin Hash Rate Index can potentially serve as the foundational pieces of financial products that can provide markets with the required tools to effectively and efficiently trade and/or hedge Bitcoin’s hash rate.
  • We welcome your feedback on how to refine these foundational pieces and pave the way for new crypto financial products. If you are a financial service provider that would like to discuss the CMBI Bitcoin Hash Rate and/or Observed Work, please reach out to [email protected]  

Introduction

With the upcoming Bitcoin halving, there has been much speculation about the impact it will have on hash rate. For the majority of the crypto community, this is a fun, speculative exercise with relatively low stakes. However, for the mining community, the outcome can not only dictate profitability but it can dictate the probability of survival. 

This is largely due to the absence of a robust, market-wide accepted methodology for hedging mining operation uncertainties. In this week’s SOTN feature, we propose two new tools that will enable financial derivative markets to effectively provide a mechanism to hedge and speculate on Bitcoin’s hash rate:

  1. The CMBI Bitcoin Hash Rate Index
  2. Observed Work

But first, a quick recap on the importance of Bitcoin’s hash rate to the cryptoasset ecosystem.

The Importance of Bitcoin’s Hash Rate

The activity of cryptoasset mining is one of Bitcoin’s core functions and was one of Satoshi Nakamoto’s key innovative ideas. Simply put, without mining, neither Bitcoin nor cryptocurrencies in general would likely exist today. Mining helps to: 

  • Secure the network, prevent corruption and disincentivize bad actors from tampering with the public ledger.
  • Mint new Bitcoin to go into circulation.
  • Order and broadcast all transactions that have occurred on the ledger.
  • Validate and append new transaction information to the ledger to allow users to transact in a trustless manner.

Miners can generally understand their costs, which are predominantly a function of Hardware / Facilities (Capex) and electricity to run the mining rigs (Opex), which, given a fixed amount of hash rate on the network, allows them to determine their ability to make a profit under particular Bitcoin price conditions. However, the total number of hashes (computing power) performed on the Bitcoin network is not constant or predictable. Rather hash power fluctuates significantly over time, and not always in line with the price of Bitcoin. 

For this reason, the ability for miners to hedge their hash rate and improve their ability to maintain profitability through a broader array of price and hash rate scenarios is critical. 

For example, consider a large institutional mining operation that is deciding whether or not to enter the market. They have the budget to acquire equipment that today will give them enough mining power to capture 1% of mining / hash rate. With this, they can expect to receive, on average, 18 BTC per day. At a price of $8,000 per Bitcoin, if the operational costs are more than $144,000 per day (at today’s reward level), a miner will not make any profits and therefore should not enter the market. However, if their operating costs are $100,000 per day, they will have a nice profit margin and should consider entering the market. 

Three months later the mining rigs arrive at the facility and Bitcoin has gone up to $10,000 per coin, but Bitcoin’s hash rate has doubled. Now they will only have 0.5% of the total hash rate, representing a reward, on average, of 9 BTC per day. At $10,000 per BTC, they will clear $90,000 per day in revenue, for a net loss of $10,000 per day, assuming a maintained operational cost of $100,000 per day. This does not bode well for the longevity of their business.

However, if they were able to hedge their exposure to mining operations by trading hash rate derivative products, they could minimize their exposure to macro shifts in hash rate. 

Note: The example utilizes illustrative figures and ignores the impact of the upcoming halving for simplicity’s sake.

Designing the Tools Required for a Hash Rate Financial Product

In a distributed process like mining, it is near impossible to obtain reliable hash rate figures from the universe of miners. Therefore, the current best practice of deriving hash rate is to generate an implied value from the rate at which blocks are produced at a given difficulty level. This approach might be like saying traders of oil futures used the price observable at gas stations to calculate the amount of oil being pumped globally. Essentially, this is deriving a price (or hash rate) right now, from historical data. 

For hash rate, this introduces many undesirable issues when creating a financial product. Coin Metrics identified three key issues with a simple hash rate index that had to be overcome:

  1. The predictability of the short term levels. Since the hash rate calculation depends on past data, the majority of the data used to generate short term future levels is already known. For example, if the hash rate is computed using a 48hr lookback window, you already have 47hrs out of the 48hrs of data points that will be used to calculate hash rate in an hour. Therefore, this short term future hash rate is relatively predictable. 
  2. Given the random block generation process, implied hash rate tends to follow an oscillating pattern (as can be observed below). This poses two types of settlement risk for contracts. Firstly, there is randomness as to whether or not a contract would settle at the top or bottom of an oscillation, which could significantly impact the outcome of a trade. Secondly, this rate is highly manipulatable by some of the large miners that control significant portions of hash rate. 
  3. A fixed contract length on hash rate does not account for what happens between the contract open and close. Imagine a 3-month contract opens and closes at the same level. If a miner wanted to hedge their position by longing this contract they would make $0 at settlement. But if the hash rate average over the period was 20% higher than the open/close rate, they also would have realized lower revenue than expected. This is a lesser consideration since, in theory, one could trade throughout the contract to overcome this, but one that could be overcome through some innovative design.

Another approach to developing derivative financial products to speculate and hedge hash rate is through the use of difficulty. While difficulty provides some benefits above a hash rate derived index, it too has some issues that need to be overcome:

  1. Difficulty only adjusts every 2,016 blocks (~2 weeks). This means that in the early parts of the contract, it is incredibly difficult to price, as estimating the future difficulty is essentially impossible and subject to significant fluctuations. 
  2. Long term difficulty contracts do not consider the difficulty levels throughout the duration of the contract. Difficulty can start and finish at the same level, but if it was higher through the middle of the contract, it does not act as an effective hedge (unless the contract has the liquidity to be managed in real time).
  3. Difficulty can be susceptible to heavy manipulation. Perhaps somewhat surprisingly, in the days before a contract closes miners can significantly impact the outcome of the next difficulty adjustment by deliberately switching off equipment.

Coin Metrics has reduced the impact of many of these issues by designing the following tools, together which can form the basis for an effective derivative market hash rate product.

1: The CMBI Bitcoin Hash Rate Index

There is no definitive way to understand the amount of hash rate that is being contributed to the Bitcoin network. Rather, an implied hash rate can be calculated by looking at the recent historical time it takes miners to produce blocks. 

Bitcoin was designed to have an average block time of 10 minutes, and every two weeks, Bitcoin’s difficulty adjusts to maintain a 10-minute average block time. Since solving for Bitcoin blocks is a random process that follows a Poisson distribution, the time between blocks can vary greatly. 

This can lead to volatility in the determination of hash rate on the network. The industry standard to date has been to view hash rate using a 24hr lookback. However, for a structured financial product, Coin Metrics deems this to be too unpredictable and volatile. For that reason, we have introduced and will leverage a 48hr lookback for the CMBI Bitcoin Hash Rate Index. 

This was especially evident when 3 blocks in a 24hr period took over 50 minutes to mine in September, resulting in the industry-standard implied 24hr hash rate to drop over 30%. However, this was just likely the result of a random, low probability but explainable outcome. Whilst the 48hr lookback period was also impacted, its <20% fall was less severe. We discuss this and more in issue 19 of SOTN

More generally, in the image above you can observe that the 48hr lookback follows a lot less volatile movements than its 24hr counterpart.

2: Observed Work

As discussed above, it was not enough to release a hash rate index given the predictability, undesired randomness (from the oscillations) and tradability issues of traditional hash rate calculations. For this reason, we created Observed Work

The traditional chainwork calculation assigns a fixed number of hashes per block based on the current difficulty (i.e. between difficulty adjustments, regardless of whether a block takes one second or one hour to find, chainwork will assign the same value). 

To better reflect the work that is done by miners and the number of hashes conducted over a fixed period of time, Coin Metrics’ Observed Work is calculated as follows:

By introducing both the implied hash rate level and the time taken to find the most recent block, this representation of work conducted is more reactive and responsive to the realities of mining activity when compared with chainwork.

Coin Metrics’ Proposed Observed Work Futures Contract

Recall from above that a miner knows the number of hashes that their equipment can produce, but not what other miners can and will produce in the future. Based on the implied hash rate, a miner understands their current share of total hash rate and thus their expected revenue / share of block rewards. 

Observed Work has been developed for financial service providers to build structured financial products:

  • For market participants to speculate on hash rate.
  • For miners to effectively manage their hash rate exposure by being able to hedge against the total observed number of hashes over a period of time. 

Bitcoin’s difficulty level provides great insight into the network’s expectations of hash rate over each 2,016 block epoch. For this reason, a financial product that utilizes Observed Work would allow users to effectively trade expectations of the number of hashes with the unknown reality of hash rate movements over fixed timeframes.

Below is a theoretical example of an Observed Work 50-minute contract (3,000 seconds), assuming:

  1. The market expects the hash rate to be 100 exahashes per second at time t=0
  2. Bitcoin blocks are expected to take 600 seconds per block as defined in the Bitcoin whitepaper

Note: The implied hash rate values are directionally correct but for simplicity use rounded and easily digestible values.

At the opening time of the contract, a reasonable expectation of settlement price would be 300,000 exahashes (3,000 seconds ✖ 100 exahashes per second). However, as evidenced below, despite the implied hash rate closing at the same level that it opened, the contract would adjust over time and close higher than expected at 308,050 exahashes.

Walking through this result block by block:

  • Block 1 takes the expected 600 seconds to be found, thus there is no change to the implied hash rate and the observed work of 60,000 exahashes equals the expected work. 
  • Block 2 is found in 10 seconds, which will increase the implied hash rate as block time was less than the protocol defined 600 seconds. At time 0, the expected work in 10 seconds was 1,000 exahashes (10 seconds * 100 exahashes per second). However, since the hash rate went up, the observed work increased to 1,050.
  • Similarly, block 3 was a fast block and therefore the implied hash rate increased and observed work was higher than what was expected at time 0.
  • Block 4 is the first slow block, taking over 600 seconds and thus reducing the implied hash rate to 105 exahashes per second. This is still higher than the 100 exahashes per second that we expected at time 0, which results in this block too having a higher observed work than expected.
  • Block 5 is another slow block, resulting in an implied hash rate of 100 exahashes per second, the same rate at which hash rate started. Given this, the observed work for this block equals the expected work, producing 119,000 exahashes.

This scenario is not uncommon in the Bitcoin protocol. One recent period that demonstrated this result very clearly was in mid-January this year (depicted below). As can be observed, the implied hash rate began and ended the 2,016 block period at approximately the same value. Despite this, the difficulty rose 5% since hash rate spent the majority of the period above expected levels. If a miner were to have taken a long hash rate position during this contract term, they would have not achieved the returns forecasted at the start of the period from their mining operation, as the average hash rate was higher than expected. Additionally, they would have made very little profit on the long hash rate futures contract because hash rate closed around the level that it opened.

However, exploring how a two week observed work futures contract over this period would have performed, it is evident from the below that:

  • The total amount of work conducted by miners throughout the period was higher than expected.
  • A miner with a fixed rate of hashes per second would have received less yield through the period than they expected.
  • If the miner was long this contract, they would have profited from the increase in observed work throughout the period.

This can further be modeled over longer contract lengths to provide long-term exposure and hedging to hash rate as may be required (e.g. hedging between ordering and receiving equipment). Below is an example 3-Month Observed Work Contract from the first difficulty adjustment of 2020. It can be visually observed how such a contract’s expectations would change over time as more information came to light and the contract settlement date got closer.

Conclusion

From the above examples, we can observe that such a structured financial product would overcome many of the issues that have hindered successful hash rate products as discussed earlier:

  1. Predictability – the work conducted during a contract is always increasing, making it less susceptible to the predictability issues that hash rate faces due to its oscillating pattern. Further, whilst expected work is well understood, the observed work that takes place is highly dependent on the randomness of block times coupled with fluctuations in hash rate. To this extent, the divergence between expectation and observed work is less predictable than short term hash rate movements.
  2. Measure performance over the duration of the contract – hash rate contracts could close at the top or bottom of an oscillation, which introduced an unwanted random risk to traders. Further, hash rate levels do not reflect the behavior of the metric over the duration of the contract. Observed work reflects the whole history of ‘work’ over the contract, and isn’t as impacted by the oscillating pattern of hash rate.
  3. Manipulability – Given the large amount of hash rate that some miners possess, they could significantly and rapidly impact both hash rate and difficulty. Observed work can improve the manipulation resistance of hash rate products by adding time-weighted dimensions that follow a random Poisson distribution.

Mining is one of Bitcoin’s core functions and innovations that has allowed us all to benefit from a decentralized, distributed and sovereignless currency. As such, hash rate is a very important on-chain metric that provides markets and network participants with an indication of network strength and security. 

To date, the critical role of miners has been unhedged and solely dependent on the price of Bitcoin. However, as the mining market continues to mature with the inclusion of VC-backed operations and traditional market participants, these companies will seek mechanisms to hedge their exposure and operations much like they do with other traditional assets.

Together, the CMBI Bitcoin Hash Rate Index and Observed Work hope to be the foundations of financial products that can finally provide markets with the required tools to effectively and efficiently trade and/or hedge Bitcoin’s hash rate. We welcome your feedback on how to refine these foundational pieces and pave the way for new crypto financial products.

If you are a financial service provider that would like to discuss the CMBI Bitcoin Hash Rate and/or Observed Work, please reach out to [email protected]  

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

The major cryptoassets had their strongest week since the Mach 12th crash, with Bitcoin (BTC) leading the way. BTC market cap grew 17% week-over-week, breaking the recent trend of Ethereum (ETH) outperforming BTC. Despite this, ETH also had a relatively strong week, with market cap growing 12.8%.

BTC and ETH usage also continued to trend upwards and recover after the crash. BTC fees are up 170% week-over-week, which signals a large surge in network demand. As a result, BTC’s fee-to-revenue ratio (a key indicator of network health) reached over 6% on April 30th, its highest level since June 2019.

Network Highlights

There is now over $1 billion of Tether issued on Tron (USDT-TRX). Over $350 million USDT-TRX has been issued since April 1st.

The following chart was generated using our free community charting tool.

Source: Coin Metrics Community Data

Additionally, there is now over $5.6 billion Tether issued on Ethereum (USDT-ETH), and $1.34 billion on Omni (USDT). If considered separately, USDT-ETH, USDT, and USDT-TRX are the first, second, and third biggest stablecoins by market cap. 

The following chart was generated using our free community charting tool.

Source: Coin Metrics Community Data

Market Data Insights

The Portfolio Allocation Challenge 

One of the interesting things about the crypto asset management industry is that there is no consensus on what to benchmark returns to. Three logical candidates have emerged: use Bitcoin only, use Ethereum as a proxy for altcoin returns, or use a market capitalization weighted index. 

Asset management in crypto is hard because not only do fund managers need to be right on how much long or short exposure to have, they also need to be right on the mix and weighting of the assets in the portfolio. Cryptoassets tend to fall into certain market regimes where one of the three candidates vastly outperforms the others, and correctly predicting which regime we are in is one of the key alpha producing decisions a fund manager can make. Depending on which benchmark you decide to use to assess fund performance, the dispersion in returns can be so large between these three candidates that it can be tough to tell if a fund is outperforming or underperforming. 

Source: Coin Metrics Reference Rates

This previous week is one instance where Bitcoin (+16%) vastly outperformed most other large capitalization cryptoassets. For the past several months, Bitcoin, Ethereum, and the long tail of altcoins have more or less performed similarly, but we are starting to be in the phase of the cycle where large divergences could be possible. 

During the last cycle that ended in January 2018, it was Bitcoin that led to first run up. After wealth was made in Bitcoin, capital was shifted to Ethereum and altcoins. Eventually, the bubble crashed in part because all remaining buyers were exhausted and because the launch of so many altcoins raised the global supply of cryptoassets to unsustainable levels. 

Tether Market Share Grows

Many respected industry observers expected Tether to fail, but it continues to defy its critics. The most salient criticisms assert that Tether would eventually crumble under its own weight due to its lack of transparency, investigations by government regulatory organizations, and its troubled banking relationships. 

What was underappreciated by the market is how these characteristics actually make Tether more useful to certain market participants. By operating in a legal gray zone and taking a stance that it will not operate in a regulatory-compliant and transparent manner, it has attracted all sorts of traders that need these protections. Tether issuance is through the roof and its lead in the stablecoin market is still unrivaled. 

Here we show Tether’s volume market share for Binance. Back when Binance launched, most volume was still denominated in Bitcoin or Ethereum. We see some declines in Tether market share in late 2018 as competing stablecoins such as USD Coin and Paxos Standard launched. But since then, Tether has crowded out almost all other cryptoassets, and the trend shows no signs of slowing down. 

Source: Coin Metrics Market Data Feed

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes had another good week off the back of continued global market strength. After a month of underperformance, the more risky low-cap assets performed the best this week, returning almost 13%. The CMBI Bitcoin Index and CMBI Ethereum Index also had strong weeks, returning 6.9% and 7.6% respectively.

After a March to forget, cryptoassets bounced back strong in May with an almost uncanny uniform performance across the top 70 assets, with the Bletchley 10, 20, 40 and Total all returning between 34% and 36%. However, it was the CMBI Ethereum Index that outpaced all other indexes, returning 58.7% in what was its second-best month in the past two years.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 48 – Creating a Better Supply Measurement: Introducing Free Float Supply

Creating a Better Supply Measurement: Introducing Free Float Supply

An accurate measure of supply is crucial in determining a cryptoasset’s value. However, the definition and methodologies of calculating supply are not yet widely agreed upon or standardized, which leads to different supply counts across the industry.

One definition of supply is “current supply”, which represents the total amount of native units that are visible on a blockchain’s ledger. This number is publicly available and accessible to any individual that downloads a cryptoasset’s blockchain ledger, which acts as a source of truth. 

However, utilizing this metric can grossly misrepresent a cryptoasset’s underlying liquidity and capitalization, as most have a certain amount of supply that is effectively out of circulation. This poses an issue for creating investable financial products such as indexes that rely on supply data to determine a constituent’s weight in a multi-asset index. 

Understanding what portion of supply is unavailable to markets can help market participants to make smarter and more informed investment decisions. Currently, the market relies primarily on the ‘Reported Supply’, which is generally provided by the asset creator and is visible on the majority of data distributor dashboards. However, in the absence of regulatory requirements or strong incentives, reporting by these entities has historically proven to be infrequent and sometimes lacking in accuracy. 

Coin Metrics recently announced the CM Free Float Supply, a new metric that is being developed to more accurately represent the supply of an asset available to the market. By applying a standardized approach, this metric represents a cross blockchain unified portrayal of the crypto market’s liquidity. For greater detail on the rationale for the methodology decisions that make up CM Free Float Supply, please refer to our blog post, Cryptoasset Free Float: An Exploration of Supply Dynamics.

CM Free Float Supply overcomes the challenges of misrepresenting supply by restricting categories of token holders that do not provide liquidity to markets. Coin Metrics’ approach to Free Float Supply determination can be represented as follows:

1 – This approach has been taken for UTXO chains as opposed to the traditional mechanism of assessing individual UTXOs for inactivity. The purpose of this is to develop a more ubiquitous and consistent approach for applying logic across all blockchains.

This approach leverages some of the best practices for supply determination from traditional capital markets and applies them systematically to cryptoassets. Many of the values produced will not be familiar at first glance, but we hope that they help provide a new and more accurate view of cryptoasset liquidity in markets. At Coin Metrics we strive to set the standard for transparent and actionable cryptoasset data, and we believe this new supply metric will aid us in achieving that goal.

Case Studies on the Free Float Supply of Different Asset Groups

Given the varying architectures and token economic models of blockchains, it was essential to create a methodology that can be applied consistently across all cryptoassets, or risk introducing large amounts of subjectivity and expert judgment that could jeopardize the usefulness of the metric. It is therefore very important that our data suite is unbiased and can be interpreted across any asset class. 

In this section, we detail how the Coin Metrics Free Float Supply Methodology has been applied across different blockchain architectures and token economic models, including UTXO chains, forked assets, and Ethereum tokens.

Case Study 1: UTXO Blockchains

Bitcoin was the original UTXO blockchain, and many others have followed since. An unspent transaction output (UTXO) blockchain is a way of structuring a ledger whereby all coins (or bundles of coins) are only spent once. A UTXO is an output that a network user receives and has the right to spend at a time in the future.

The early UTXO chains are very simple to audit as most were launched with no pre-mine (i.e. private mining by select participants before the source code is released to the public to mine), no ICO, no foundation, and thus very few restrictions on their supply.

In the calculation of BTC’s free float supply in our free float methodology explanation blog, we considered send and receive transactions as the sign of an active address. However, after further investigation and internal deliberation, we have improved our approach and consistent treatment of the methodology across blockchains by only considering send transactions specifically as signs of activity. The rationale behind this is that for a small cost, supply values could be easily manipulated.

Note, this change has now been applied to all UTXO blockchain supply figures, and as such the below BCH and BSV values have been improved from previously reported values as well.

Both Bitcoin and Litecoin had no ICO, issued no founding team tokens and had no pre-mine. But both chains are over five years old and thus have UTXOs that have not been touched in over five years. As such, in both instances, five years into the chain’s existence, you will notice the divergence of Free Float Supply from Current Supply.

Bitcoin has 4.1M BTC unmoved tokens in over five years and Litecoin has 3.0M LTC unmoved in over five years that have been excluded from the CM Free Float Supply.

Note: Reported Supply is currently the most quoted industry value that is generally the value observable on a blockchain or as reported by a foundation where one exists.

Case Study 2: Hard Forked Blockchains

A hard fork can occur when a change in consensus rules results in non-backward compatible software. If any network participants decide to run their own version of the blockchain’s software that creates a different set of consensus rules, a new blockchain with its own native token will be created.

These new native tokens are not only credited to the holders of the parent chain, but they carry the full history of the parent chain as well. Despite this, given the pseudonymity of cryptoassets, it is difficult to understand who these token holders are and predict what their actions will be. For example, are they aware of their right to claim their tokens, and do they know how to claim? As such, assuming the full history and financial ownership of the parent chain may not accurately reflect the realities of the forked chain. 

Coin Metrics has taken a conservative approach and excluded all tokens from addresses on the newly forked blockchain that have never been activated since the time of the fork. Activation here is defined as an address that sends any amount of their assets (or UTXOs), thus proving that all tokens in that address are owned and monitored.

Ethereum Classic (ETC) was the first hard fork that met the criteria as outlined in the Coin Metrics Fork Legitimacy Policy. Interestingly, activation of ETC native units after the fork was extremely high. Currently, addresses that hold over 97% of tokens have been transacted post fork. 

Similar to Bitcoin, Bitcoin Cash (BCH) and Bitcoin SV (BSV) do not have any foundation wallets, founding team tokens, provably lost tokens (>0.1%), burned tokens (>0.1%), vesting tokens, or pre-mine. However, despite the publicity and media attention surrounding both forks, they did not receive the same amount of activation that the Ethereum Classic fork did. Bitcoin Cash addresses holding 6.4M BCH and Bitcoin SV addresses holding 8.5M BSV remain untouched since the time of their forks.

Case Study 3: Stellar and XRP

For both Stellar and XRP, foundations have, to date, held the majority of the current supply. As such, Coin Metrics has identified a significant amount of restricted supply. Both foundations and founding team member wallets have historically demonstrated relatively high levels of activity (i.e. token selling) which has continually resulted in increases in their free floats.

In the case of XRP, all foundation and team tokens identified and all escrowed tokens have been removed to determine the free float. There were no identified provably lost tokens (>0.1%) or burned tokens (>0.1%) still present on-chain. 

Stellar is similar. To Coin Metrics’ knowledge, there are multiple Stellar Development Foundation (SDF) wallets, tokens that are vesting (in the SDF) and tokens that are burned. These tokens have been removed to determine the XLM free float. 

Case Study 4: Ethereum Tokens

Most tokens launched on Ethereum, including Ether (ETH), were released through an Initial Coin Offering (ICO). The majority of these projects allocate significant portions of the current supply to the foundation and team members. Foundation tokens are often utilized to fund long-term growth initiatives and can remain within foundation wallets for extended durations. Team member tokens can be subject to vesting schedules early on, but in many cases, founding team members hold the majority of their tokens longer term.

Ethereum launched in 2015 with a relatively small foundation and team token allocation. Since then, many of the tokens have been moved and sold. The Ethereum foundation now only holds around 0.5% of the total ETH supply. A further 1.0% has been identified as founding team tokens and 0.5% was provably lost in the Parity wallet bug. 

Chainlink is a typical cryptoasset born from the modern day ICO, where fewer than half of all created tokens were distributed at genesis. Upon launching, the Chainlink foundation and the founding team members held 65% of the token’s current supply. Since launch, there has been some movement from founding team wallets that has increased the free float supply from 350M to 379M.

Applying Free Float

The CM Free Float Supply is designed to generate and maintain the most accurate representation of cryptoasset liquidity across the market. Coin Metrics is able to do so by hosting our own nodes that allow for detailed on-chain analysis and the real-time tracking of specific tagged addresses. Further, hosting nodes and managing data allows Coin Metrics to independently verify all information from cryptoasset foundations and teams through on-chain forensics and verification. 

Whilst it may seem unfamiliar to consider the supply of Bitcoin as 14.3M or Bitcoin Cash as 12.0M doing so can provide some significant benefits when conducting market wide analysis and designing portfolios. Through better representing the supply and demand relationship of cryptoassets across the market, portfolio managers can reduce tracking error, unnecessary portfolio rebalance costs and slippage, and the management effort required. 

To that extent, CMBI market cap weighted indexes will leverage the CM Free Float Supply to create a suite of highly investable indexes that accurately track and represent the underlying cryptoasset market. These CMBI Indexes will provide markets and customers with industry leading solutions that aid in performance benchmarking and asset allocation.

Network Data Insights

Summary Metrics

Ethereum (ETH) had another strong week as it continues to rebound after the March 12th crash. ETH market cap increased by 9.0% week-over-week, and realized cap grew by 1.2%. Adjusted transfer value, transfer count, and daily fees all also showed solid growth, signaling that Ethereum on-chain activity is increasing along with the market cap.

Bitcoin (BTC) also had a relatively strong week, with market cap growing by 4.3%. BTC transaction fees grew by 34.2% week-over-week, which is BTC’s strongest week of fee growth over the last month.

Network Highlights

Tezos (XTZ) and Chainlink (LINK) market caps have both grown by over 70% over the last 30 days. Zcash (ZEC) and Ethereum (ETH) have also rebounded well, growing 51% and 48%, respectively.

More than one million Ethereum smart contracts have been created since March 12th. The number of smart contracts deployed on Ethereum grew from 13.36 million on March 12th to 14.41 million on April 26th. 

For context, the number of Ethereum smart contracts increased by about 470K between January 1st and March 12th.

Market Data Insights

All large capitalization cryptoassets saw gains this week with Tezos (XTZ), Stellar (XLM), and Cardano (ADA) managing gains in excess of 20%. One of the key portfolio level decisions for investors in the space is the relative allocation between major assets like Bitcoin and Ethereum versus the allocation to the longer tail of assets. Accurately determining which market regime we are in and how the various market capitalization segments will perform is important. Recent market activity has shown us some isolated examples of certain cryptoassets in the longer tail exhibiting outperformance with high beta to Bitcoin’s returns — a trend that deserves continued observation. 

Bitcoin volatility measured on a one month rolling window has almost completely reverted to normal levels. For the past few years, an annualized volatility of around 50% seems to be a critical level. Volatility rarely goes below this level and oftentimes bounces higher off it for brief periods of heightened volatility.

Usually lower volatility will cause investors to become more complacent and use more leverage, but the market crash on March 12 may have led to a longer lasting change in trader behavior. Implied volatility levels also have almost completely reverted and open interest on the major perpetual swap contracts are still down from recent highs. Volatility will likely remain muted until the memory of March 12 has faded somewhat and risk taking using leveraged financial instruments comes back. 

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes performed well this week as global markets continued to rally after the early March crash. The CMBI Bitcoin Index and the CMBI Ethereum Index returned 6.9% and 7.6% respectively, but it was the small-cap Bletchley 40 that was the strongest performer, returning 12.9% week-over-week. 

The strength of the cryptoasset performance was experienced across the market, evidenced by all even weighted indexes outperforming their market cap weighted counterparts. 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 47 – Assessing the Long-Term Fallout from Crypto’s Black Thursday

Assessing the Long-Term Fallout from Crypto’s Black Thursday

by Antoine Le Calvez and the Coin Metrics Team

On March 12th 2020, now called “Black Thursday,” Bitcoin’s price dropped by nearly 50%, one of its largest drops since the Mt. Gox debacle.

Source: Coin Metrics Reference Rates

In our 43rd issue, we looked at the impact of that price drop on the crypto market structure – specifically, we explained how BitMEX’s liquidation engine could have amplified the drop, the lingering impact on liquidity left by the crash, and how stablecoins seemed to have gained from it.

In this issue, we’ll look at the impact of Black Thursday on on-chain data and exchange market share.

Transaction Fees

One of the immediate impacts of the Black Thursday drop was on transaction fees. As traders rushed to move coins in and out of exchanges in order to add margin to positions or to profit from arbitrage opportunities, the demand for block space heated up.

Most Bitcoin wallets use dynamic fee estimation, and txstats.com’s archives of these estimates allow us to see how they reacted to the increase in activity (txstats.com is presented in partnership with BitMEX Research). Fee estimates for rapid confirmation (10-20 minute wait time) went from 27 satoshis/byte of transaction data to 70 sats/byte in just a few hours.

Source: txstats.com

More surprisingly, median transaction fees measured in dollars for both Bitcoin and Ethereum shot up almost five-fold. Bitcoin’s fees remained elevated for two weeks while Ethereum’s fees recovered in two days.

Black Thursday highlighted in red. | Source: Coin Metrics Network Data Pro

Overlaying Bitcoin’s block space utilization (i.e. block weight used as a proportion of block weight available per block) shows that fees stayed elevated following Black Thursday despite block space utilization returning to normal levels.

Black Thursday highlighted in red. | Source: Coin Metrics Network Data Pro

What explains this discrepancy? One possible explanation is that the lingering effect on transaction fees could indicate the presence of a feedback loop between the various fee estimation APIs. Similar to how traffic jams form from a single clog in the system, a single and brief perturbation can have effects far outlasting it.

BitMEX

Black Thursday’s drop stopped when BitMEX, the leading Bitcoin futures platform prior to Black Thursday, experienced a denial-of-service attack. This led to many theories as to why the price recovered after BitMEX went offline, with the most prominent being explained in State of the Network Issue 43.

Following that fateful day, the number of Bitcoins held by BitMEX (on behalf of traders) first rapidly increased then dropped significantly over the following two weeks, stabilizing recently.

Black Thursday highlighted in red. | Source: Coin Metrics Network Data Pro

There could be many explanations as to why this happened. The early increase could have been caused by traders depositing coins to either trade the very high volatility or add margin to existing positions to avoid liquidation.

This is visible by looking at the distribution of deposits to BitMEX. On the 12th and 13th, the 90th percentile of deposits, by value, jumped several fold indicating that traders made larger deposits to BitMEX.

Black Thursday highlighted in red. | Source: Coin Metrics

As for the long drawdown, two main things can potentially explain it:

  • BitMEX lost some market share following Black Thursday
  • Crypto traders are deleveraging and withdrawing their remaining unused trading capital

One way to test the first hypothesis is to look at BitMEX’s market share in Bitcoin futures markets:

In both open interest (size of futures contracts held by traders) and in volume, BitMEX lost market share following Black Thursday. The biggest market share winner was Binance futures:

As for the deleveraging part, aggregate open interest fell by 50% in a single day and still hasn’t recovered (although it’s been slowly and steadily rebuilding since it bottomed).

Conclusion

It’s been more than a month since Black Thursday and while most of its immediate impact has now faded away with volatility reducing and spreads tightening, some of the longer term consequences are only starting to become visible.

Notably, since the crash there has been a reshuffling of the top futures marketplaces for crypto assets with BitMEX losing some of its market share to Binance. This may have an on-going impact across crypto markets, especially considering BitMEX’s outsized influence on price discovery. Only time will tell if BitMEX is able to recover the lost market share, or if the marketplace is undergoing a true changing of the guard.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) usage showed signs of growth this past week. BTC daily active addresses  grew 12.1% week-over-week, and topped 900K on both April 7th and April 15th. The last time BTC had more than 900K daily active addresses was in June 2019.

Bitcoin Cash (BCH) usage, on the other hand, declined over the past week. Active addresses dropped by over 46% week-over-week. Additionally, BCH estimated hash rate continues to decline after its April 9th halving.

Network Highlights

Stablecoins have gained another $1B in market cap since the start of April. Most of the growth continues to come from Tether issued on Ethereum (USDT_ETH) which went from a market cap of $4.43B on April 1st to $5.14B on April 19th.

The following chart was created using Coin Metrics’ community charting tool, which you can access for free here.

Source: Coin Metrics Community Data

Stablecoin transfers also continue to rise, with USDT_ETH once again leading the way. Although daily transfers for USDC, BUSD, and DAI all peaked on March 18th, daily transfers for USDT_ETH and PAX have continued to rise. USDT_ETH has grown from about 83K daily transfers in the beginning of November 2019 to about 141K daily transfers as of April 19th.

Source: Coin Metrics Network Data Pro

USDT_ETH transfer count has been growing faster than both BTC and ETH over the last 180 days. Although BTC and ETH both still have significantly more daily transfers, USDT_ETH transfer growth has had a noticeable uptick since mid-March. 

Source: Coin Metrics Network Data Pro

Market Data Insights

ETH leads all large cap assets this week with a 13% gain. As noted in the Network Highlights section, issuance of stablecoins designed using the ERC-20 standard and transfers of stablecoins on the Ethereum network continue to grow strongly. Given these developments, one of the more interesting debates right now is whether stablecoin growth is good or bad for ETH. 

Stablecoins are increasingly becoming critical tokens to the cryptocurrency industry and dozens of projects have been launched. The vast majority of projects have chosen to launch as ERC-20 tokens on ETH which should further solidify the ERC-20 standard and strengthen a network effect that is difficult for competing standards to overcome. When examining the first order impact, stablecoin growth should increase the demand for ETH because every stablecoin transaction requires ETH for transaction fees. 

On the other hand, as stablecoins become increasingly used, there is the potential for stablecoins to lower the monetary premium of ETH. ETH has a credible claim as money within the crypto space, but stablecoins challenge this view. Stablecoins have the potential, due to their lowered volatility, to become the store-of-value, medium of exchange, and unit of account for crypto transactions and smart contracts that need to store value. This is already beginning to happen at the margin, such as MakerDAO adding USDC as an option to serve as collateral in Dai loans. 

This week the narrative is that stablecoin growth is good for ETH, but it will be interesting to see the evolving impact of these competing forces. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

Across the board, cryptoasset markets performed strongly through the week as reflected by all the Bletchley multi-asset indexes. The CMBI Ethereum Index was the strongest performer through to April 19, returning 10.4%, whilst the CMBI Bitcoin Index finished the week flat. The small-cap assets yielded the highest returns for the week, with the Bletchley 40 returning 7.1%, followed by the Bletchley 20 (mid-cap assets) which returned 6.2%.

The highest performer of the even indexes was the Bletchley 40 Even, which returned 6.4%, indicating that the strong performance of small cap assets was spread across all constituents within the index and not just a select few.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 46 – Investigating Bitcoin’s Changing Correlations

Is Bitcoin an Uncorrelated Financial Asset, A Safe Haven Asset, or Both?

Investigating Bitcoin’s Changing Correlations

By Nate Maddrey and the Coin Metrics Team

The narratives about Bitcoin’s value have shifted over the years, and continue to be debated today. At different points, Bitcoin has been described as electronic cash, censorship resistant digital gold, and an anonymous darknet currency.

Source: Visions of Bitcoin

Among all of the competing narratives there are two that are particularly important when considering Bitcoin as an investment or store of value:

  1. Bitcoin is an uncorrelated financial asset
  2. Bitcoin is a safe haven asset

But data/analysis about these theories is often lacking. In this week’s State of the Network we analyze end-of-day and intraday correlations between Bitcoin and stocks and gold to test these popular narratives.

Methodology

To calculate the correlations in this report, we first took the natural log returns for each asset and then calculated rolling Pearson correlations over specified time periods. We analyzed end of day correlations using New York close pricing (4:00 PM EDT) over a 250 day rolling time window. We also looked at intraday correlations by looking at 5 minute returns over a 60 hour rolling time window.

Since cryptocurrency markets never close but equity markets close on nights and weekends, we cut out Bitcoin results for the days/hours when equity markets were closed and stitched together the results. This helps remove some noise, but has a side effect of sometimes creating exaggerated correlations around the opening/closing of each market day.  

Data sources include Coin Metrics, Finnhub, and FRED. You can check out Bitcoin (and other cryptoasset) correlation charts in our free community charting tool, although the numbers will be slightly different due to the different methodology used for this piece. 

Uncorrelated Financial Asset 

Bitcoin’s correlation with other financial assets is an important consideration when analyzing it as an investment option. If Bitcoin has low correlation with traditional financial assets like stocks, it can effectively be used as a portfolio diversifier. 

The stock market is large and complex, and it can be difficult to analyze Bitcoin’s true correlation with the stock market as a whole. One relatively simple way to examine correlations with stocks is to look at Bitcoin’s correlation with the S&P 500 index (specifically SPY), which can serve as a proxy for the stock market at large. 

Historically, Bitcoin has been relatively uncorrelated with the S&P 500. Since 2012, Bitcoin/S&P 500 correlation has generally stayed between about .15 and -.15, which signals little to no correlation.

But over the last month, Bitcoin/S&P 500 correlation has suddenly increased to new all-time highs. The following chart shows end-of-day correlation calculated on a 250 day rolling basis. 

On a more granular level, intraday data shows that correlation peaked on Black Thursday (i.e. March 12th), when the crypto markets and equity markets both experienced historic, sudden losses (see State of the Network Issue 42 for our analysis on how the crash was mostly driven by short term holders). Correlation then decreased back to relatively normal levels by the end of March. But since then it has started to climb again.

Does this signal that Bitcoin and the S&P 500 are now suddenly correlated?

Probably not. Although short-term correlation shot up, it was under very unique market circumstances. As news about the spreading COVID-19 pandemic began to grow more and more dire on March 12th, investors across the world suddenly began rushing to cash and selling off assets en masse. As a result, correlation shot up between most assets on March 12th. 

For example, the correlation between SPY and GLD suddenly shot up to its highest since 2013. This was likely due to the liquidity crunch caused by the pandemic, which led to sell-offs across the board.

Over the last year, Bitcoin and the S&P 500 have had a correlation close to zero. The following chart shows distribution of intraday correlation (5 min returns, 60 hour rolling correlation) over the last 365 days. It’s relatively centrally distributed around 0, with a mean of -.0075. This shows that under normal market conditions, Bitcoin and the S&P 500 are not significantly correlated.

Bitcoin fundamentals did not change over the last month. However, the outside world changed significantly. Over the long-term, Bitcoin and S&P 500 correlation are likely to revert to the mean and return to levels of near zero (unless there are fundamental changes in Bitcoin and/or the S&P 500). But over the short-term, or at least as long as the liquidity crisis lasts, there may continue to be a relatively high correlation between the two, since global conditions appear to be influencing both markets. 

Safe Haven Asset

Another popular narrative is that Bitcoin is a safe haven asset. Generally speaking, a safe haven is an “investment that is expected to retain or increase in value during times of market turbulence”. Gold is traditionally used as the primary example of a safe haven asset. In uncertain times, the price of gold often increases relative to other asset classes. 

Historically, Bitcoin and gold have not had a very strong correlation. But Bitcoin and gold correlation also suddenly increased in March, similar to Bitcoin and S&P 500 correlation. 

Although gold is typically considered a safe haven asset under normal market conditions, like most other asset classes gold had a relatively large sell-off on March 12th due to the liquidity crisis. Bitcoin and gold correlation increased as prices for both dropped on March 12th (although the price of both dropped, correlation increased positively since both assets were moving in the same direction). But interestingly, they have stayed relatively highly correlated since.

Although Bitcoin and gold may not act as safe havens during a global liquidity crisis, they may act as a safe haven during increases in monetary inflation and quantitative easing. Given the recent $2 trillion+ injection from the Federal Reserve and the unprecedented uncertainty of global health and economic conditions, it is possible that Bitcoin is acting as a safe haven in response to some events but not to others, and potentially even changing day to day. However it is still hard to draw strong conclusions given the huge confounding factor of the global pandemic.

Bitcoin and gold correlation also showed similar signs of growth earlier in 2020. As covered in State of the Network Issue 33, correlation increased in January as Bitcoin and gold prices both increased as US/Iran military tensions escalated. This suggests that Bitcoin may have reacted as a safe haven asset similar to gold, at least temporarily.  

These are small pieces of evidence that the correlation between Bitcoin and gold may be growing. However, Bitcoin’s overall correlation with gold is still relatively weak.

The following chart shows distribution of intraday correlation (5 min returns, 60 hour rolling correlation) between Bitcoin and gold over the last year. It’s also relatively centrally distributed around 0, but has a mean of 0.1194, which is slightly higher than the mean of the Bitcoin/S&P 500 correlation distribution.

Conclusion

Historically, Bitcoin has not been very highly correlated with stocks or gold. Although correlations recently reached all-time highs, it is unlikely that Bitcoin and S&P 500 correlations will remain elevated in the long-term without major changes in the fundamentals of one or both markets. But there is some evidence that correlation between Bitcoin and gold may be starting to increase, at least slightly.

Although the short-term is still uncertain amidst the global pandemic, this could potentially be a long-term inflection point for Bitcoin if federal banks around the world continue to inject money into the global economy at historic rates.  The following chart shows BTC correlation with the 5-Year Forward Inflation Expectation Rate (T5YIFR) from the St. Louis. Fed. Theoretically, if Bitcoin is used as a safe haven in times of monetary inflation, Bitcoin prices should go up as expected inflation increases (and vice versa). Interestingly, Bitcoin/T5YIFR correlation also shot up on March 12th, as the Fed sprung into action in response to the global pandemic

We will continue to follow the situation as it unfolds, and provide context around Bitcoin’s changing narratives. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Ethereum (ETH) metrics surged this past week, with active addresses growing 15% week-over-week. ETH realized cap increased 1.6% from the previous week, its first significant increase since the March 12th crash. 

Bitcoin Cash (BCH) also had a big week, with hash rate and difficulty falling due to the scheduled block reward halving. The BCH halving also led to a significant spike in activity, with active addresses and transfers growing 39.3% and 60.6%, respectively.

Network Highlights

Ethereum-issued Tether (USDT-ETH) usage continues to climb. On April 7th, USDT-ETH reached 143.32K daily transactions, the highest daily total since September 2019. The April 7th transaction count also eclipsed the 145.71K transactions on March 13th in the direct aftermath of Black Thursday. Omni Tether (USDT) and Tron Tether (USDT-TRX) both still have significantly less daily transactions than USDT-ETH.

Source: Coin Metrics Network Data Pro

The amount of BTC held by Bitfinex has been dropping since April 2nd. Bitfinex BTC supply had declined by about 24% over the last 30 days, which almost matches BitMEX’s 26% decrease. 

Source: Coin Metrics Network Data Pro

Simultaneously, the amount of ETH held by Bitfinex has increased by 13% over the last 30 days, which is a larger percentage increase than any other exchange in our coverage. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Markets are up solidly for the week with high correlation among cryptoassets but meaningful dispersion in returns. Most large capitalization cryptoassets outperformed Bitcoin this week. If this pattern sustains, it could foreshadow a change in the market regime where smaller cryptoassets experience a higher beta to Bitcoin. Chainlink (+53%) and Tezos (+21%) are outperformers for the week. 

Cryptoasset volatility is off its recent highs as global financial markets stabilize in response to the use of monetary policy tools designed to provide liquidity by virtually every major central bank around the world. 

Source: Coin Metrics Reference Rates

Stablecoins across the board have all seen dramatic increases in their issuance over the past month or so. The drivers of this increase have been a bit of a mystery, with some market participants pointing to an increased need of stablecoins to ride out market volatility, some pointing to continued growth in the lending market for stablecoins, and others pointing to increased retail activity and dip-buying behavior on exchanges. 

Here we examine a broader macroeconomic driver for stablecoin issuance: a global shortage of U.S. dollars. Over the past several decades, the dollars’ status as the global reserve currency has been unrivaled. Meaningful amounts of global commerce is invoiced in dollars, major commodities are priced and transacted in U.S. dollars, and large amounts of U.S. dollar denominated foreign debt has been issued by foreign companies and governments. Under normal circumstances, these foreign entities need a steady supply of dollars to engage in trade and to service their debts. 

Now, with disruptions on both the demand and supply side in global trade, the torrent of dollars from the U.S. to the world has declined to a small stream. The situation is especially acute now because dollars are needed as a store of value to ride out volatility and for margin calls as leveraged positions unwind. Dollar strength, as measured by the trade weighted U.S. dollar index, jumped nearly 8 percent in a few days starting on March 10. 

On the margin, stablecoins should benefit from the global shortage of dollars. USD Coin, the second largest stablecoin, saw its supply increase by over 50 percent in just a few days, also starting on March 10 as the dollar shortage became severe and the dollar strengthened. 

The dollar has since given up some of its gains as the Fed has instituted dollar swap lines with major foreign central banks to make sure foreign entities and institutions have access to the dollars they need. In response, USD Coin issuance is also showing signs of slower growth. 

Source: Coin Metrics Network Data Pro

CM Bletchley Indexes (CMBI) Insights

In designing the CMBI market cap weighted indexes, Coin Metrics have recently released commentary on many of our methodology decisions for determining the ‘free float’ (circulating) supply of cryptoassets. Information can be found in our blog article, Cryptoasset Free Float: An Exploration of Supply Dynamics, released last week.

All CMBI and Bletchley Indexes finished the week positive for a third week running, but still far from recovering from their mid March drop. The CMBI Ethereum Index was the strongest performer, returning 14.5% over the week. Mid cap cryptoassets were the best performing market size group, with the Bletchley 20 returning 12.4% for the week and being the only market weighted index to perform better than Bitcoin. 

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • In designing market-cap-weighted indexes, the primary goal of a benchmark administrator is to provide the most accurate representation of the underlying market by creating a robust methodology and leveraging high-quality data. For an in-depth exploration of our index methodology check out our recent blog article: Cryptoasset Free Float: An Exploration of Supply Dynamics.
  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 45 – The Signal and the Nonce Redux: From S9s to S17s

The Signal and the Nonce Redux: From S9s to S17s

By Karim Helmy and the Coin Metrics Team

As Bitcoin enters its next halving, the network is experiencing several simultaneous transitions. In addition to the severe change in mining economics being caused by the reward adjustment, Bitmain’s Antminer S17 is in the process of replacing the longstanding S9 line of miners as the dominant mining hardware on the network. The first rig in the S9 line, the eponymous Antminer S9, was released by Bitmain in 2016 and quickly became the most popular SHA-256 miner; as a result, the network has not experienced such a shift in years. 

Due to a lack of publicly available data about the types of mining hardware used by individual miners, it can be difficult to measure the rate at which this transition is occurring. One unexpected source does shed some light on mining hardware trends, though: the network’s nonce distribution. The arrangement of these arbitrary numbers, included by miners as part of each block’s hash, hints at how mining hardware usage has shifted over the years.

In a previous issue of state of the network, we investigated how nonce distributions patterns can be used to spot the rise of ASICs. In this issue, we’ll dig further into the peculiarities of Bitcoin’s nonce distribution and the sources behind the distribution’s striations to investigate the recent shifts in mining hardware. We’ll then break down this data by mining pool, which allows for more granular insight into the hardware used by specific pools.

Golden Marbles – Understanding The Mining Process 

Mining is a critical part of Bitcoin’s security model and arguably the most important improvement on previous attempts at creating digital money. Although the implications of mining are quite complex, the concept behind it is relatively simple to understand.

From the perspective of a miner, mining a block resembles repeatedly selecting marbles from a bag without replacement. In this analogy, the number of marbles is very large, with a large proportion of blue marbles and a small proportion of gold marbles. Miners receive a payout on pulling a gold marble from the bag.

Explained in more technical terms, Bitcoin miners compete to find a golden nonce that, when appended to the header of a proposed block, hashes to below a certain value determined by the network’s difficulty parameter. Miners search for this nonce, or arbitrary number, that can only be used once, by guessing values and checking if the resulting hash is below some threshold. The first miner to find such a value for a valid block and broadcast it to the network receives the right to choose and order the transactions within the block, a necessary step for these transactions to be eventually considered valid. 

In return, the miner also receives a payout from the block reward and fees from any transactions included in the block, both of which are received in a special coinbase transaction. Provided that the purported properties of the SHA-256 hash function hold, the distribution of golden nonces for any given block is random and a golden nonce cannot be found except through brute-force computation.

Because a reference to the coinbase transaction is included in the block header, each mining entity is sampling from a different distribution. In other words, each entity is pulling marbles from a different bag, where bags contain the same number of marbles and, in expectation, the same ratio of blue and gold marbles.

The proportion of golden marbles is determined by the network’s difficulty parameter, and is fixed for the relevant period. The difficulty parameter is automatically adjusted by the network. Today, due to a high block difficulty and random variance, there are often no golden nonces for a specific block header. In other words, there are some bags that contain no golden marbles. 

Miners who exhaust the nonce space of a proposed block typically increment the block’s timestamp to generate a new set of nonces. That is to say, when a miner runs out of marbles, they grab a new, full bag. If the timestamp has reached the point where further adjustment would render it invalid, the miner must adjust the set of transactions included in the block. Analogously, if a miner runs out of bags in their room, they need to grab some more from another room, which is time-intensive.

To increase their probability of finding a golden nonce in a fixed period of time, miners can parallelize their computations, which is analogous to pulling marbles by the handful rather than one at a time. Nonce-finding can be parallelized by using hardware suited to the task, in particular graphical processing units (GPUs) and specialized chips known as ASICs. ASICs are much more efficient at parallelization than any alternative, and today account for virtually all of the network’s computational power, or hashpower.

In another form of parallelization, several miners coordinate their nonce-finding and agree to split any payouts. This strategy reduces both the size and variance of a miner’s payouts, and does not change expected long-run revenue. Groups of miners acting in this way are known as pools. The operator of a pool typically charges a fee, which individual miners accept in exchange for a reduction in income volatility.

Bitcoin’s Nonce Distribution

Every two weeks, Bitcoin’s difficulty parameter is adjusted so that a new block would be produced every ten minutes on average if the amount of computation performed on the network were to remain constant. This feature ensures the network will continue to operate in spite of potentially large changes in hashpower. In a sufficiently competitive mining market dominated by miners who are computing values in parallel, then, we would expect the plot of golden nonces over time to look like evenly distributed static. Surprisingly, it doesn’t.

The non-random distribution near the left-hand side of the plot can be attributed to mining by iteratively testing values starting at 0. If a miner is mining without parallelization on a CPU and as an individual, and therefore has no possibility of running collisions with other members of their pool, this strategy is as valid as any other, since the nonce distribution for each new block is independent. The disappearance of this pattern coincides with the introduction of GPU miners, which parallelize computation.

Near the right-hand side of the plot, there is a striated pattern of regions with very few nonces. To our knowledge, this anomaly was first noticed by Twitter user @100TrillionUSD in January of 2019. The same plot, with the striated region labeled, is shown below.

The bizarre pattern was the subject of a BitMEX research piece shortly after, which speculated that the anomaly was the result of a quirk in an implementation of AsicBoost, a controversial mining optimization technique.

There are two variants of AsicBoost: covert AsicBoost, which cannot be definitively observed on-chain, and overt AsicBoost, which can be. The BitMEX research team discusses both variants, but is particularly interested in the effect of covert AsicBoost, the use of which was made practically impossible for non-empty blocks with the activation of SegWit in August of 2017. The researchers could not confirm their hypothesis. 

The streaked pattern indicates that miners are systematically undersampling certain ranges of possible nonces. By excluding certain ranges from sampling, miners are effectively partitioning their marbles into a small number of different bags and refusing to pull from certain bags. In expectation, the color ratio of each bag is equal, so miners do not change the probability of selecting a golden marble on the first try by doing this. Because the number of marbles in each bag is very large, the reduction in effectiveness caused by adopting this strategy when sampling repeatedly is small. This strategy does, however, increase the frequency with which miners must grab a new bag of marbles, which can be expensive. Since each mining entity is sampling from their own distribution, other pools cannot use knowledge of an entity’s adoption of this technique to their advantage by strategically sampling.

In October of 2019, State of the Network Issue 23 looked at Bitcoin’s nonce distribution in depth and noted the streaked pattern. Since then, the striated pattern has faded, and the nonces of recently-mined blocks appear to be more randomly distributed.

The anomalies in the nonce distribution do not appear to be directly related to AsicBoost. Covert AsicBoost became unusable in 2017, and the first firmware update enabling overt AsicBoost was publicly released in October of 2018, but the striations are clearly visible between these two dates. Additionally, while overt AsicBoost usage remains high, the patterns are no longer visible in blocks mined either with or without overt AsicBoost.

Instead, the patterns in the nonce distribution may be caused by the manner in which Bitmain’s Antminer S7 and S9 families of miners sample nonces. This artifact is likely an unintended side-effect of optimization, and is ultimately harmless to both the miner and the network.

The S7 and S9 lines contain several related models using the BM1385 and BM1387 chips, respectively. The period in which each line of miners was dominant on the network corresponds to a distinct phase in the patterning of Bitcoin’s nonce distribution.

When observing all nonce values on the network, the streaked pattern first becomes clear in late 2015, coinciding with the release of the S7 in late August of that year and the fulfillment of orders in late September.

The Antminer S9 was released in late May of 2016, with the purchasers of the first batch receiving their orders in mid-June of that year. Shortly afterward, the streaks become more narrow in concurrence with supersession of the S7 by the S9 as the dominant miner on the network in late 2016.

The pattern’s recent breakdown coincides with the transition from the S9 to the Antminer S17 as the dominant miner on the network. While the S17 was released in April of 2019, the use of S9s on the network has until recently remained common as they have continued to be economical to operate.

Pooled Analysis

Stratifying the dataset by each block’s miner allows for a more fine-grained view of the nonce distribution. Identifying the miner of a block is relatively straightforward but carries several caveats.

The miner of a block is typically identified through a tag left in the block’s coinbase data field. These identifiers are voluntary and falsifiable: miners are not required to leave a message, and may choose to leave another pool’s tag in place of their own. In certain situations, these misleading behaviors may even be incentivized, so the shortcomings of this approach should be recognized. This technique is the industry standard, however, and while many miners choose not to leave an identifier, we have no reason to believe that falsification is occurring on a significant scale.

The miner of a block is labeled according to their most recent identifiable block mined. This provides robustness against anomalies like hashpower voting, in which the coinbase data is used to signal support for a fork rather than to identify the miner.

Mining entities are also identified through reuse of a known payout address. This approach requires pools to reuse addresses, and is sensitive to the initial seed set of known addresses. For our purposes, this approach is used to supplement tagging based on the coinbase data in order to provide coverage for miners who do not leave a consistent tag.

Once we have categorized blocks by miner, we can incorporate this information into our plot of Bitcoin’s nonce distribution.

We can also take a look at the nonce distribution of individual pools. Even at this level, the anomalous patterns remain visible. Consider the plot below, which shows the blocks mined by Antpool and BTC.com, both of which are owned by BitMain, as well as ViaBTC, in which BitMain is an investor.

The streaked patterns are significantly clearer in the nonce distributions of Bitmain-affiliated pools than in that of the network as a whole. This indicates a higher proportion of S7s and S9s in these pools during the relevant period, which is to be expected given the pools’ association with the manufacturer of these miners.

The proportion of blocks mined by unknown entities shows a large drop-off in 2015. This is a result of the block size wars, during which many previously anonymous miners began to identify themselves on-chain in order to signal support or opposition to a block size increase. Today, the vast majority of miners by hashpower are identifiable. The striated patterns are faintly visible in the nonces of blocks mined by unknown miners, as is their gradual dissolution.

Conclusion

The Antminer S9 has until recently been the most-used miner on the Bitcoin network since its release in 2016. Despite the release of the S17 last year, the S9 remained economical to operate for a period, but the miner is being phased out in light of increasing hash rate and changing market conditions. The shift in dominance from the S9 to the S17 that is currently taking place in anticipation of the halving has not been properly considered in many analysts’ assessments of the network.

In parallel with miners’ transition from predominantly using the S9 to the S17, the streaked patterns that were formerly the defining feature of Bitcoin’s nonce distribution have dissolved. The source of these mysterious streaks, which appear in a space that should look random, has been the subject of significant speculation. The timing of the streaks’ visibility lends credence to the theory that these lines were an artifact of the hardware used to mine on the network, in particular the S9 and the S7 that preceded it.

Nonce data allows us to gauge the scale and pace of this shift, using only public information, in a manner that would otherwise be impossible. By taking advantage of the artifacts left by the S9 in the sampling of nonces, we may be able to estimate the proportion of these miners on the network. The segregation of this data by pool gives unique information on the efficiency of miners’ operations, to be covered in a future report. This issue paves the way for a formal assessment of this type.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) mining showed healthy signs of recovery this past week with estimated hash rate increasing by 7.3%. Inefficient miners have likely already started to capitulate and are being replaced by more efficient miners, which is positive for the long-term health of the network. For more on miner economics and the implications of the recent difficulty decrease, see State of The Network Issue 44 – Understanding Miner Economics From First Principles

BTC active addresses also showed positive signs of recovery this week, growing by 6.3%. But Ethereum (ETH) active addresses went in the opposite direction, dropping by 13.4% week-over-week. ETH daily active addresses peaked at 537K on March 21st, the highest daily total since May, 2018. However, since then they have been declining – ETH had 310K daily active addresses on April 5th.

Network Highlights

The number of addresses holding relatively small amounts of BTC has been increasing since the March 12th crash. 

The number of addresses holding between one billionth (1/1B) and one hundred millionth (1/100M) of the total BTC supply (i.e. between 0.000000001% and 0.00000001% of total supply) has increased about 6% over the last 90 days. Similarly, the number of addresses holding between one hundred millionth (1/100M) and one ten millionth (1/10M) of total supply increased about 4%. 

Both had a noticeable increase in growth rate beginning around March 12th. This could signal that adoption is growing, as new users start acquiring relatively small amounts of BTC.  

Source: Coin Metrics Network Data Pro

The amount of ETH held by the exchanges in our coverage (listed below) has grown over the last 30 days, while the amount of BTC held by exchanges has decreased. 

ETH has increased by about 5%, while the amount of BTC held on exchanges has decreased by about 3%. The drop in BTC is largely due to the rapid decrease in supply held by BitMEX, as covered in the Network Highlights section of State of the Network Issue 44.

The below chart shows the 30 day growth for the total supply held on the following exchanges: Bitfinex, Binance, Bitstamp, Bittrex, Gemini, Huobi, Kraken, BitMEX, and Poloniex.

Source: Coin Metrics Network Data Pro

Bitfinex has had the largest increase in ETH supplies out of all of the exchanges in our coverage. The amount of ETH held by Bitfinex has increased by about 17% over the last 30 days, while no other exchange has had more than a 10% increase. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Markets are up sharply over the past week and are beginning to recover losses sustained on March 12. Our previous research finds that this sell-off was driven by short-term holders and reinforced by the BitMEX liquidation spiral. A broad consensus is forming that this sell-off, mirroring the sell-off seen in traditional markets, was at least in part due to technical dislocations in the market. Sentiment among retail investors appears to be unaffected as evidenced by increased user activity from Coinbase

Source: Coin Metrics Reference Rates

The “risk-on asset” versus “safe haven asset” debate continues over Bitcoin. Some market participants have observed that Bitcoin’s safe haven narrative has been damaged over the past month which negatively impacts institutional investors’ appetite for entering the space. 

A closer examination of Bitcoin and gold provides some evidence that the narrative is intact and could be stronger than ever. While Bitcoin did sell off aggressively in concert with equity markets, gold did too due to forced liquidations that happened in nearly every financial market. Since then, both Bitcoin and gold have recovered some of their losses. 

Source: Coin Metrics Reference Rates

Bitcoin’s correlation with gold, measured over the past 30 days, is now at all time highs. Unprecedented monetary policy and fiscal stimulus from nearly every country in the world is forming the base for a credible narrative of increased risk of severe financial imbalances and the potential for long-term increases in inflation. Ultimately, these fears never materialized during the 2008 financial crisis, but conditions are ripe for these fears to resurface again. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

CMBI and Bletchley Indexes all had a great week with ~15% increases across the board. The Bletchley 40, small-cap assets, performed the best of the market cap weighted indexes through the week, returning 16.9%. Interestingly the lower weighted assets within the Bletchley 40 were the top performers, demonstrated by the large returns of the Bletchley 40 Even and the Bletchley Total Even Indexes. For reference, the even indexes weigh all constituents equally, giving more weight to the smallest cap assets within the index.

The relatively low returns of all CMBI and market cap weighted indexes against BTC further demonstrates the uniformity of the week’s performance across the asset class. 

Despite the strong performance of cryptoassets this week, monthly returns were still down significantly through March, with all CMBI single asset and Bletchley market cap weighted indexes down over 20%. The CMBI Ethereum index was the worst performer through March, falling 40.5% from $224.25 to close the month at $133.39. 

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 44 – Understanding Miner Economics From First Principles

Understanding Miner Economics From First Principles 

By Kevin Lu and the Coin Metrics Team |Tuesday, March 31st, 2020

The next halvening is approaching, yet debate about its impact on asset prices remains mired in controversy. 

Two camps have formed. One believes the halvening is already priced in by market participants, citing the efficient market hypothesis. The other camp believes it isn’t yet fully priced in and expects the halvening to plant the seed for further increases in prices due to the increase in perceived scarcity and the change in supply-side dynamics.  

Source: Coin Metrics Network Data Pro

We believe the intensity of the debate partially stems from the limited empirical record. Bitcoin has only experienced two halvings in its history and only a handful of other proof-of-work coins have gone through the same events. Discussions are stalled because of the lack of shared terminology, small sample size, and inaccessible data regarding critical questions. 

In this week’s State of the Network, we present a framework for understanding miner economics and how to best navigate the upcoming block reward halving. The intention is to present a framework reasoned from first principles rather than relying purely on empirical data. We also apply this framework in examining the upcoming halving for Bitcoin, Bitcoin Cash, and Bitcoin SV. 

Three Miner Axioms and Inferences 

We present a set of three miner axioms which we believe to be largely true as a starting point for further reasoning. We say “largely true” because there are always edge cases — they may not hold for certain assets or for certain miners. But for the most part, these axioms hold water. 

We also present three miner inferences that are built upon our three axioms. These inferences form the foundation of our framework for understanding miner economics. 

Axiom 1 

Miners operate as profit-maximizing commercial enterprises with large economies of scale

Mining has gotten so difficult and resource-intensive that is largely uneconomical for an individual or hobbyist to participate. Instead, there are large economies-of-scale to mining. Large miners locate themselves in areas of the world where electricity is cheap. They are able to negotiate lower rates with electricity utility companies, purchase large quantities of the most efficient mining equipment, and rent large facilities to operate the equipment. 

The ability to mine at scale lowers the cost of mining a single coin. And since mining is a competition, miners organize as a profit-maximizing commercial enterprise. Miners do not operate for ideological or altruistic purposes and cannot continue operating in the long-term if they are not profitable. 

Axiom 2

Mining is a competition with a fixed total reward that is split among all participants with a regular cadence

Issuance is mandated by the protocol and controlled via a difficulty adjustment. In the case of Bitcoin, the protocol generates a block reward of 12.5 coins per block (currently) and regularly adjusts mining difficulty such that blocks are generated on average every 10 minutes. All miners compete for this reward, along with transaction fees. The total block reward revenue for all miners over a given period of time is predetermined and cannot be changed except for marginal amounts and for brief periods of time between difficulty adjustments. 

Axiom 3

Miner revenue is denominated in crypto while miner costs are denominated in fiat 

Miner revenue consists of the block reward and transaction fees, both of which are denominated in crypto. 

Mining costs include mining hardware, electricity to operate the miners, cooling fees, facility rental fees, server maintenance, internet connectivity, salaries, insurance, legal services, taxes, and so on. These costs are denominated in fiat since most traditional companies do not currently accept crypto as payment (electricity utility companies will not take Bitcoin as payment, for example). Even if certain expenses end up being paid using crypto, such as instances where miners pay for equipment or employee salaries using crypto, the price of the good or service is still quoted in fiat currency. 

Inference 1

Mining is a (Nearly) Perfectly Competitive Industry 

Based on the first two axioms above, the first inference we introduce is that the mining industry operates under an equilibrium of nearly perfect competition where the market price faced by each miner equals the miner’s marginal cost. This is achieved by two mechanisms. 

First, profit-maximizing miners enter the industry or invest in more equipment when mining is profitable and exit the industry or turn off miners when it is unprofitable. Second, the change in hash rate triggers a difficulty adjustment which constantly seeks to bring the cost of mining a single coin equal to the current market price. 

Mining is zero-sum (in the long-term) in that each miner is in competition with other miners over the same block reward. This also means that miners operate in an equilibrium state of zero economic surplus — that is, in the long-run, miners earn only normal profits and are compensated only for the opportunity cost of their time plus an allowance for risk. Due to the competitiveness of the miner economy, it seeks a long-term equilibrium where miners profit margins are small and close to zero. 

Miner profit margins, however, can meaningfully fluctuate around this equilibrium due to delays inherent in the system which has important implications on miner-led selling pressure. We discuss this more in the following two inferences. 

Furthermore, the industries that reside upstream to mining such as miner hardware and semiconductor manufacturers show elements of oligopoly market structure. Based on this supply chain, certain miners (such as the Bitmain affiliated mining pools) can leverage information advantages or access mining hardware earlier than their competitors which reduces the degree of perfect competition in the mining industry.

Inference 2

Miners Are a Continuous and Significant Source of Selling Pressure

Combined with the third axiom, we present an important inference: miners represent the single largest cohort of natural, consistent sellers. Their selling pressure is significant because miners must sell the crypto that they earn to cover their fiat-denominated costs. And since their profit margins tend to gravitate towards zero, miners must sell nearly all of the crypto that they earn. 

Here we use Bitcoin to contextualize the magnitude of miner-led selling pressure. Miner revenue in 2019 was nearly $5.5 billion dollars. Some researchers compare this number to the annual trading volume of Bitcoin, which is several magnitudes bigger, and conclude that miner-led selling pressure has a negligible impact on the market. However, selling from miners represents net capital outflows from the space and the fiat obtained by miners is unlikely to ever return to the market, which is not necessarily the case for other trading volume. Therefore, miner selling has an outsized influence on the rest of the market

Put differently, the best estimates indicate Coinbase has roughly 1 million Bitcoin in customer deposits. At current prices, this is equivalent to $6.8 billion dollars, an amount similar to annual miner revenue in 2019. Under the assumption that miners sell the majority of the crypto they mine, miner-led selling pressure is nearly equivalent to all customers on Coinbase liquidating their Bitcoin over the course of a year and permanently exiting the market. 

Source: Coin Metrics Network Data Pro

We extrapolate miner revenue for the entire year of 2020, assuming prices remain at current levels and accounting for the halving of the block reward. Under these assumptions, we should only see half-of-a-Coinbase worth of selling pressure this year — a significant reduction. 

Inference 3

Miners Have a Pro-Cyclical Impact on Asset Prices 

While the mining industry is constantly seeking a long-term equilibrium where miner profit margins are small but close to zero, the reality is that profit margins experience large fluctuations around this steady state. 

Elements influencing the cost side of the equation are slow moving and react with a meaningful lag. Decisions regarding entering or exiting the industry, purchasing additional equipment, and scaling up operations all take time. And difficulty adjustments by their nature have an approximately two week lag. 

On the opposite side, revenue is fast moving because one of the main determinants is the price of the coin which is subject to extreme levels of volatility. Bitcoin regularly experiences annualized volatility of over 50 percent. 

Source: Coin Metrics Reference Rates

Varying profit margins due to these factors mean that the amount of selling pressure by miners to cover their fixed, fiat-denominated costs varies as well. When prices are particularly volatile or trend in one direction over a sustained period of time, miner profit margins can be consistently positive or negative for meaningful amounts of time. These deviations are more likely to occur when prices are rising, since delays regarding more capital investment in mining hardware are more prominent compared to delays when prices are declining. The decision to shut off miners when prices fall below electricity costs can be made quickly. 

Inventory management of miners is not a well-studied topic since access to this information is not available, but it stands to reason that each miner makes their own decision on how much of their block rewards to sell for fiat and when to sell it. Since miner variable costs are slow moving and fairly constant in fiat terms, miners are required to sell less of their block rewards to cover their expenses during periods of rising crypto prices. 

On the other hand, when crypto prices are falling, they are required to sell more. Under this theory, miners have a pro-cyclical effect on the market, in that they further exacerbate price increases. There are limitations to this dynamic, however. Sustained increases in prices can compel miners to sell more of their block rewards to fund additional capital investment in new mining hardware suggesting a counter-cyclical impact on prices under certain market conditions. 

During periods of capitulation where profit margins for many miners are negative, miner-led selling flow is likely to be high. Miners may attempt to endure periods of short-term pain, and perhaps may temporarily operate at a loss until less cost-efficient miners exit the industry. Miners may be willing to sell block rewards earned in prior periods that they kept on their balance sheet to be used in an attempt to outlast other miners. 

All of these behaviors reinforce the direction in which crypto prices are moving and are a key determinant in why crypto prices regularly experience bubbles and crashes. 

While we believe this framework characterizes the pro-cyclical behavior of most miners, the rise of a robust lending market has the potential to change this dynamic. This allows miners to speculate on the future price of Bitcoin and engage in market timing where they pay for their fiat expenses using borrowed funds that are collateralized with the Bitcoin on their balance sheet. Miners that engage in this behavior believe that Bitcoin’s price will rise in the future and delay selling. The rise of a derivatives market which allows miners to hedge against future price movements can play a similar role. 

While the overall impact on the amount of miner-led selling flow depends on how accurate miners are in their market timing efforts, we believe that miners will tend to borrow fiat under certain market conditions. Assuming that miners intrinsically have a long-bias for Bitcoin, miners will tend to borrow fiat when they believe prices are well below the long-term fundamental value and when they believe we are firmly in a bull market. This should moderate the pro-cyclical impact when prices are declining but accentuate the impact when prices are increasing. 

The Upcoming Halving 

Bitcoin will soon experience its third halvening where the block reward will be reduced from 12.5 coins per block to 6.25 coins per block, equivalent to annualized issuance being reduced from 3.6 percent to 1.8 percent. This is anticipated to occur in approximately 45 days or May 14, 2020. 

Source: Coin Metrics Network Data Pro

Prices have sharply declined over the past several weeks in concert with risk assets in traditional markets. The pro-cyclical behavior of miners implies that miner-led selling pressure should be increasing as well. Prices have almost certainly declined below the breakeven price for the set of miners who are least efficient and have the lowest profit margins. These miners have likely either temporarily or permanently shut off their machines. This can be seen in the most recent difficulty adjustment where difficulty declined by 16 percent, one of the largest drops in history.

Source: Coin Metrics Network Data Pro

Such a large difficulty adjustment indicates that inefficient miners are already reaching a point of capitulation where they are forced to sell all the coins they mine to cover their costs. 

Miner-led selling pressure for Bitcoin is likely to continue to increase because both Bitcoin Cash and Bitcoin SV will be experiencing their halving on April 8 and April 9, respectively. All three assets share the same SHA-256 mining algorithm and miners can seamlessly redirect their hash power to the asset that provides the highest return on investment. 

When Bitcoin Cash and Bitcoin SV halve their block rewards, this should force miners to direct even more hash power to Bitcoin as it will still have a 12.5 native unit block reward (instead of 6.25) for about a month longer. Therefore, we should expect difficulty increases for Bitcoin that should further squeeze profit margins for all miners. 

Source: Coin Metrics Network Data Pro

It is concerning that miners are in a state of capitulation even before the halving. Once the block reward halves, miner revenue will be cut in half while miner costs will remain constant, so we expect even more miners to capitulate in the months ahead. 

Miner capitulation increases selling pressure until inefficient miners are forced off the network, but in the long run these events are supportive for prices. Culling inefficient miners allows only the most efficient miners with the lowest cost of production to remain. Once inefficient miners exit the network, profit margins will improve for the remaining miners, which reduces selling pressure, increases prices, and should repeat in a virtuous cycle. Eventually, if prices bottom and recover, the pro-cyclical behavior of remaining miners should support further price increases. 

Conclusion 

Using a set of axioms, we provide a framework reasoned from first principles that illustrates how miners are a continuous and significant source of selling pressure that has a pro-cyclical impact on prices. Miner-led selling pressure for Bitcoin, Bitcoin Cash, and Bitcoin SV is currently high and is likely to increase further in the coming months as all three coins undergo their halvings.

We expect miners to follow a cycle of decreased profit margins, increased selling, capitulation, and a culling of the least efficient miners from the network. Once this cycle is complete, the miner industry should return to a healthier state that is supportive of future price increases. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

The major cryptoassets remained relatively stable this past week. Although market cap increased, realized cap stayed stable or dipped for all five assets in our sample. The ratio of realized cap to market cap (MVRV) can be used to help gauge market tops and bottoms, and also gives insight into the behavior or holders vs speculators, as explored in State of the Network Issue 41.

Bitcoin’s estimated hash rate rose week-over-week after plummeting in the aftermath of Black Thursday, which led to Bitcoin’s second largest difficulty percentage drop in history. Although fees have been down this past week, mining revenue increased due to Bitcoin’s price gains. 

Network Highlights

Binance USD (BUSD) market cap has almost tripled since March 1st, increasing from about $68M to over $181M. Huobi USD (HUSD) market cap has almost doubled, growing from $78M to $136M.

The following chart was created using our free community charting tool. We recently added BUSD and HUSD to fill out our stablecoin data set.  

Source: Coin Metrics Community Charts

Tether also continues its rapid growth. There has been $1.4B worth of Tether issued on Ethereum (USDT-ETH) since March 1st. Tron-issued Tether’s (USDT-TRX) market cap has increased by about $165M since March 1st, while Omni-issued Tether (USDT) has stayed relatively stable. Tether’s total market cap is now over $6.4B

Source: Coin Metrics Network Data Pro

The amount of Bitcoin held by most exchanges has decreased over the last 30 days. Out of the exchanges in our coverage, only Kraken and Bitfinex have increased their BTC supply over the last month (1% growth each). 

Source: Coin Metrics Network Data Pro

The amount of Bitcoin held by BitMEX has been in freefall over the past two weeks after experiencing mass liquidations on March 13th (see State of the Network Issue 43 for our coverage on the BitMEX liquidation spiral). As of March 29th, BitMEX held 244k BTC, down from a peak of 315k on March 13th. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Most cryptoassets remained largely unchanged over the past week but with significant volatility. Bitcoin and other coins continue to show intermittent periods of high correlation with risk assets, particularly during pre-market trading. Volatility remains at high levels with Bitcoin’s rolling one month volatility at 148%, nearly the same level as during the late 2017 bubble. 

Source: Coin Metrics Reference Rates

Stablecoins are seeing large increases in issuance but their pegs to the U.S. dollar remain relatively stable outside of an unstable period on March 12. The reason for the increase in issuance across the board is still unknown, but stablecoins do not appear to be selling at a meaningful premium. While most stablecoins remain close to the $1 U.S. dollar peg (with the exception of Dai), there appears to be a small but marked regime shift between and after March 12. Stablecoin prices and bid-ask spreads appear to have entered a more volatile regime. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

Cryptoasset markets had a turbulent week with most CMBI and Bletchley Indexes experiencing intraweek highs of over 10% above last week’s close. However after a strong start to the week, all indexes fell significantly through the weekend, but still managed to finish up between 0-5%. 

The Bletchley 40 (small-cap) finished the week strongest, up close to to 5% against the U.S. dollar and 3.5% against Bitcoin. All Bletchley multi-asset indexes outperformed the CMBI Bitcoin and CMBI Ethereum single-asset indexes this week. 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • We are happy to announce that we completed a $6 million round of funding led by Highland Capital Partners with participation from FMR (Fidelity Management & Research), LLC, Castle Island Ventures, Communitas Capital, Collaborative Fund, Avon Ventures, Raptor Group, Coinbase Ventures, and Digital Currency Group.
  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 43 – The BitMEX Liquidation Spiral

The BitMEX Liquidation Spiral – Analyzing How Crypto’s Nascent Market Structure Held Up During the Crash

By Antoine Le Calvez and the Coin Metrics Team

In the previous issue of State of the Network, we presented some preliminary analysis of the recent dramatic crash in cryptoasset prices. We showed that on-chain data seem to indicate that few long-term Bitcoin holders capitulated when Bitcoin’s price dropped by nearly 40% in a single day.

Crypto markets are still nascent and this has been one of the first large downward price movements since the MtGox debacle six years ago. Since then, many new exchanges have sprung up, derivatives products have emerged and the amount of capital allocated to trading cryptoassets has skyrocketed.

In this feature, we’ll look at how the markets held under the pressure from the recent sell-off and whether crypto’s unique market structure exacerbated the problem.

The BitMEX Liquidation Spiral

Two large Bitcoin price moves occured on March 12th and 13th which were registered by Coin Metrics’ Real Time Reference Rate:

  • On March 12th, from 10:00 to 11:00AM UTC, Bitcoin’s price fell from $7,300 to a low of $5,690. 
  • From March 12th 11:00PM to March 13th 2:15AM, Bitcoin’s price fell from $5,800 to a low of $3,900.

One exchange played a particularly pivotal role during the second price drop: BitMEX.

BitMEX (Bitcoin Mercantile Exchange) is one of the largest new derivatives markets that emerged post-MtGox. It created the “perpetual inverse swap”, a financial product allowing leveraged trading of dollar-denominated Bitcoin perpetual futures contracts using Bitcoin as margin collateral.

Created in 2014, BitMEX’s popularity grew immensely and by March of 2020 it handled billions of dollars of trading volume per day. Studies have shown that its flagship perpetual contract is critical to Bitcoin’s price discovery.

On March 13th, during the second downward price movement at 2:16AM UTC, trading on BitMEX slowed to a crawl as the exchange faced what was first thought to be a hardware issue, but was later determined to be an intentional DDOS attack. This made it nearly impossible to trade on BitMEX.

As soon as BitMEX was attacked, the price recovered and surged to $5,300.

The red area indicates when BitMEX suffered DDOS attacks.

From March 12th 9AM to March 13th 6AM UTC, long positions worth 1.1B contracts (one contract represents a $1 position) were liquidated. As traders got liquidated, the open interest (the number of contracts held by traders) decreased:

BitMEX allows leveraged trading of Bitcoin, but also guarantees that no trader can lose more than their margin (i.e. you cannot lose more than what you bet). In traditional markets, this is often not possible. BitMEX achieves this using two features. 

First, if a position gets liquidated (its remaining margin is not high enough), an automated system takes over the position: the liquidation engine. Run by BitMEX, it aims to close the trader’s position at a price favorable enough that not all the remaining margin gets used. If it manages to do so, the profits go to an insurance fund. If it doesn’t, funds get withdrawn from that insurance fund (which stands at more than 30k BTC as of writing). 

The second feature is auto-deleveraging. If the liquidation engine cannot close liquidated positions profitably and the insurance fund runs low, it resorts to taking money from traders with winning positions to cover losses from losing positions. This is the last recourse, as arbitrarily changing traders’ positions on one exchange can affect their overall financial health since they often run strategies on many other exchanges. Following this crash, BitMEX posted a good in-depth explainer of these mechanics. 

This bloodbath was partially stopped when BitMEX suffered a reported DDOS attack. This led many to wonder whether the crash was partially caused or aggravated by the exchange’s handling of all the liquidated positions.

The theory goes as follows:

When long positions get liquidated, as was the case when the price went down, the engine has to sell contracts. As liquidations mounted and liquidity waned, the engine was put in a difficult spot: it had lots of contracts to sell, but faced a worsening price leading to more liquidations and more contracts to sell. This can create a vicious cycle that is difficult to stop.

When trading on BitMEX became very difficult due to the DDOS attack, the biggest seller on the market, BitMEX’s liquidation engine, disappeared and the price naturally went up.

A Lingering Impact on Liquidity

A common way to measure market conditions is looking at the bid-ask spread, which is the difference between the best bid (i.e. the price a buyer is willing to pay) and the best ask (i.e. the price a seller wants to receive). It is commonly measured in basis points (0.01% equals 1 basis point or bps).

For Bitcoin, still an emerging asset class and with varying fees per trading venue, the bid-ask spread is mostly below 20 bps in normal trading conditions. This can be seen across three exchanges in the chart below, observed from February 1 to 3 of this year:

Source: Coin Metrics Market Data Feed

Large price movements directly affect the bid ask spread as market makers react to the volatility by widening their bids and asks. In the next chart, we can see the impact of a price drop from $9,500 to a low of $8,000 in the span of 2 hours in September 2019  (the Y-axis is capped at 50bps to make this more visible):

Source: Coin Metrics Market Data Feed

Once the move is over and the price stabilizes, the spreads come back to their pre-move levels.

The March 12th-13th move was different. Spreads still haven’t come back to their previous levels.

Source: Coin Metrics Market Data Feed

There could be multiple explanations as to why spreads haven’t come back to pre-March 12th levels. Market participants could be expecting volatility to continue and are preparing themselves by increasing their spreads. Bitcoin’s realized volatility measured over the past one month is at the high end of its historical trading range over the past six years. 

Source: Coin Metrics Reference Rates

It could also be that some market participants left altogether, reducing liquidity. For example, futures open interest hasn’t grown following the market crash and bid-offer spread for a $10M quote has grown significantly:

Source: Coin Metrics Market Data Feed

Stablecoins Galore

The supply of all stablecoins Coin Metrics tracks started growing around the time COVID-19’s impact on global markets started to be visible (S&P all-time-high was on Feb 19th). It seems that the growth of stablecoins’ supply increased after Bitcoin’s massive drop.

Source: Coin Metrics Network Data Pro

The dual impact of Bitcoin’s USD value halving and massive issuance of stablecoins led to stablecoins’ market cap as a percentage of Bitcoin’s doubling in a matter of days:

Source: Coin Metrics Network Data Pro

Conclusion

This recent market move was spectacular, the largest in Bitcoin’s modern history. It had many implications: spreads on spot and futures markets widened, on-chain fees spiked as people rushed to deposit coins, and stablecoins gained market share.

It also raised many questions: should circuit-breakers be instituted? Is Bitcoin really a store of value if its value can drop in half in a matter of hours or is this merely a function of nascent market structure? 

While a lot of these questions are still unanswered, one is getting closer to having an answer: Huobi has recently implemented a liquidation circuit breaker on all their derivatives products. Despite its name, it isn’t a traditional circuit breaker in which trading stops if the traded product’s price drops too quickly. Instead of stopping trading, it throttles the liquidation engine to avoid vicious liquidation cycles. It is still unclear whether this would prevent any such cycle. It could also end up exposing the exchange to large losses if the drop in price was warranted and not caused by its liquidation engine.

While the price mostly recovered, this event left lasting marks on Bitcoin’s market structure from spreads to concerns about its stability. BitMEX might have lost traders’ confidence, as the number of Bitcoin it holds has been steadily decreasing since the crash.

Times of stress and sudden change often lead to innovation and restructuring. Crypto market structure will likely continue to be tested during these turbulent times, and will hopefully mature and grow stronger as a result.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Most usage and security metrics were down for the major cryptoassets this past week as the dust began to settle following the March 12th crash. Notably, Bitcoin transactions are down over 14% week-over-week, more than any other large cryptoasset. This is at least partially because Coinbase introduced transaction batching on March 12th, which helped reduce transactions and lighten the load on the Bitcoin blockchain. 

Also of note, Ethereum active addresses increased by almost 17% week-over-week while decreasing for all other cryptoassets in our sample. This may be due to the increase in usage of Ethereum-based Tether (more on this in the “Network Highlights” section).

Bitcoin estimated hash rate fell 12.1% over the week, as mining revenue tumbled due to the drastic price decrease. As a result, it looks like Bitcoin difficulty will likely readjust to its lowest level in 2020 at the next difficulty retarget. 

Network Highlights

Stablecoin transfer value hit an all-time high amidst the market turmoil. On March 13th, the aggregated transfer of all stablecoins that we track (listed below) reached a new all-time high of $444.21M. 

The following chart shows the total transfer value (smoothed using a seven day rolling average) for the following stablecoins: Tether issued on Omni (USDT), Ethereum (USDT-ETH), and Tron (USDT-TRX), DAI, PAX, USDC, TUSD, and GUSD.

Source: Coin Metrics Network Data Pro

Money continues to pour into stablecoins as investors look for stability amidst volatile price action. USDC has been the biggest gainer percentage-wise, with a 57% market cap increase over the last 30 days. USDC is mainly used on Coinbase but is now also being used as collateral on MakerDAO in addition to other DeFi applications.

Source: Coin Metrics Network Data Pro

MakerDAO made the decision to add USDC as a collateral option (in addition to ETH and BAT) after the price of their own decentralized stablecoin, DAI, increased to as high as $1.06 on March 12th. DAI’s destabilization was the result of a mass MakerDAO collateral liquidation. As of March 22nd, DAI price remains above $1.02. 

GUSD also slipped off of its $1 peg over the past two weeks. Its price is less than $0.98 as of March 22nd.

Source: Coin Metrics Network Data Pro

Tether issued on Ethereum (USDT-ETH) has also had a large increase in market cap, and now accounts for over 50% of the total stablecoin market cap out of the stablecoins that we cover. USDT-ETH market cap has increased by over $660M since March 10th to $3.7B as of March 22nd.

Source: Coin Metrics Network Data Pro

Market Data Insights

After starting the week down, Bitcoin rallied to finish up 9% on the week. The major Bitcoin forks (Bitcoin Cash and Bitcoin SV) also finished the week strong, up 13% and 28% respectively. Most other cryptoassets are up or relatively unchanged for the week. 

Source: Coin Metrics Reference Rates

Recent coronavirus-related events have provided more evidence in understanding Bitcoin’s unusual reaction function. After selling off in concert with global equities two weeks ago, leading to the highest correlation between Bitcoin and the S&P 500 in its history, it has since experienced a few days with less correlated movement. 

Source: Coin Metrics Community Charts

Bitcoin’s inconsistent correlation with the S&P 500, with some days being highly correlated and some days being completely independent, suggest that its reaction function is still not fully understood. The common explanation that Bitcoin is a risk-off asset during periods of negative growth shocks is compelling and appears to fit some of the facts. The other commonly cited explanation is that fiat-based bills, debt servicing requirements, and margin calls combined with the de-risking of portfolios has led to a liquidity crisis, which in turn has contributed to the Bitcoin sell-off. 

We examine an alternative explanation based on inflation expectations. Here we show the five year inflation expectations. Five years forward is a standard barometer of where market participants think inflation is heading in the long-term. 

During normal times, we see inflation expectations well-anchored around the Fed’s two percent inflation mandate. But over the past week, inflation expectations have cratered as the economic impact of the coronavirus has been realized and as oil prices (a key determinant of headline inflation) have declined. This is happening despite unprecedented monetary policy stimulus by the Fed and most central banks around the world. 

One of the main reasons why we are so interested in Bitcoin is because it is a store-of-value, especially in environments where there are high levels of inflation. Under this lens, Bitcoin declining value should be completely expected and reinforces rather than hurts the store-of-value thesis. 

Source: Federal Reserve Bank of St. Louis

CM Bletchley Indexes (CMBI) Insights

Despite the dreariness of global markets that continue to reel from the impacts of COVID-19, CMBI and Bletchley Indexes managed to claw back some of last week’s significant losses. The CMBI Bitcoin index was the strongest performer of the week, returning 11%, with the CMBI Ethereum Index experiencing the slowest recovery, only jumping 1%. 

Despite Bitcoin’s strong performance, the Bletchley 40, small-cap assets was the best of the multi-asset indexes, demonstrating Bitcoin was an outlier among its large-cap peers.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 42 – Data Shows Cryptoasset Sell-off Was Driven by Short-term Holders

Data Shows Cryptoasset Sell-off Was Driven by Short-term Holders

by Nate Maddrey and the Coin Metrics Team

On March 12th, amidst growing concerns over the COVID-19 pandemic, Bitcoin (BTC) suffered one of its largest one-day price drops in history. The rest of crypto followed, with most major assets down over 30% on the week.

Source: Coin Metrics Reference Rates

In this special edition of State of the Network, we take a deep dive into on-chain and market data to analyze the aftermath of the historic crash.

BTC & S&P Correlation Reaches New All-Time High

BTC’s historic price drop was concurrent with the equity markets’ worst day since 1987

On March 12th, the Pearson correlation between BTC and the S&P 500 soared to a new all-time high of 0.52. The previous all-time high was 0.32. This suggests cryptoasset markets are becoming more intertwined with existing markets, and are reacting to external events more than we have ever seen before. 

The following charts are sourced from our community charting tools which you can access for free here.

Source: Coin Metrics Community Data

Over the past week, BTC price has seemingly reacted to several key events, including President Trump’s announcement of a thirty day travel ban between the United States and Europe, as well as the Federal Reserve’s announcement that interest rates would be cut to 0.00%-0.25%. 

Source: Coin Metrics Reference Rates

BTC Sellers Appear to Mostly be Short-term Holders 

On-chain data shows that recent price movements were likely mostly driven by shorter-term and relatively new holders.

Coin Metrics’ revived supply tracks how many old coins come back into circulation after being untouched for a specific period of time. For example, thirty day revived supply tracks how much supply is moved on-chain (i.e. transacated) after being untouched for at least thirty days. 

On March 11th, about 281k BTC that had been untouched for at least thirty days were revived. But only 4,131 BTC that had been untouched for at least one year were revived. This signals that a vast majority of the activity on March 11th and March 12th involved BTC that had been held for less than a year. 

Source: Coin Metrics Network Data Pro

March 11th was the fourth largest spike in BTC thirty day revived supply over the last eight years. 

Source: Coin Metrics Network Data Pro

But long term holders appear unfazed in spite of the severe market downturn. March 11th’s one-year revived supply was not unusually large, as seen in the below chart. 

Source: Coin Metrics Network Data Pro

Transfer value days destroyed paints a similar picture. Transfer value days destroyed multiplies transfer value by the amount of days that the coins being transferred last moved on-chain. This gives older coins a much higher weight. For example, a coin that had not been transacted in 100 days is weighted 100x more than a coin that had been transacted 1 day ago.

There was not a significant spike in BTC transfer value days destroyed on March 11th or March 12th. This signals that there was not a relatively high amount of long-held coins moved prior to the recent price action.

Source: Coin Metrics Network Data Pro

Additionally, BTC SOPR dropped to 0.843 on March 12th, the lowest it’s been since February of 2012. In essence, SOPR is a network-wide indicator of profit/loss. It is the ratio of price sold (the price of BTC at the time new outputs are created) over the price paid (the price of BTC at the time a transaction’s inputs were created). Therefore a SOPR below one signals that investors are selling at a loss. 

Source: Coin Metrics Network Data Pro

BTC MVRV Drops Below One

For only the fourth time in history, BTC market value to realized value (MVRV) dropped below 1.0. MVRV compares a cryptoasset’s market cap to its realized cap. Realized cap can be thought of as an estimation of the asset’s aggregate cost basis.

As we wrote about in State of the Network Issue 41, an MVRV above one can signal that speculators have a higher average market valuation than holders. An MVRV below one, on the other hand, can signal that holders have (or had) a higher market valuation than current speculators. Holders are tested when MVRV swings below one, as it becomes less and less likely they will be able to immediately sell their holdings at a profit.

BTC MVRV fell by 0.5 on the 12th, which is the largest one-day drop since December 2013. In hindsight, the past periods where MVRV dropped below one have been the best times to accumulate BTC at a relatively discounted price.

Source: Coin Metrics Network Data Pro

The large drop in MVRV was caused by BTC’s market cap dropping by over 30% since March 9th, while realized cap has only dropped by about 3% (again suggesting that older coins were not being sold).

Source: Coin Metrics Network Data Pro

Realized cap dropped for all major cryptoassets. Ethereum (ETH) and Tezos (XTZ) were hit especially hard, with 6.09% and 9.12% drops, respectively, since March 9th. Maker (MKR) was the biggest loser with a massive 21% realized cap drop after MakerDAO was forced to weigh an emergency shutdown after the drastic decrease in ETH price. 

Source: Coin Metrics Network Data Pro

Money Pours Into Exchanges and Stablecoins

While market cap for most cryptoassets fell, the market cap for most stablecoins increased. This potentially signals that investors are piling into “cash,” or at least crypto cash equivalents. 

Ethereum-issued Tether (USDT_ETH) market cap increased by about $300M from March 10th through March 15th. USD Coin (USDC), which is used on Coinbase as well as other platforms, also had a huge gain, growing close to $150M in market cap since March 10th. 

Source: Coin Metrics Network Data Pro

On March 13th, over 160k BTC flowed into the exchanges in our coverage universe, which includes Binance, Bitfinex, BitMEX, Bitstamp, Bittrex, Gemini, Huobi, Kraken, and Poloniex. This was the largest one-day inflow since November 13th, 2017.

Source: Coin Metrics Network Data Pro

Similarly, over 171k BTC flowed out of exchanges on March 13th, which was the largest daily total since November 2017.

Source: Coin Metrics Network Data Pro

BitMEX, which is a leading destination for futures trading, had the most inflows out of the exchanges in our coverage, with 43.2k and 37.5k of BTC inflow on March 12th and 13th, respectively. 

Source: Coin Metrics Network Data Pro

Both Binance and Huobi, however, had more daily outflows than BitMEX. 

Source: Coin Metrics Network Data Pro

As a consequence, the amount of supply held by BitMEX soared to an all-time high. On March 13th, the amount of BTC held by BitMEX peaked at 315.7k.

Source: Coin Metrics Network Data Pro

A large spread of around 16% was observed between BitMEX and Coinbase during the sell-off. This is likely because forced liquidations from leveraged perpetual swap futures tend to exaggerate the direction of any move. The market recovered after BitMEX went down for 23 minutes reportedly due to unscheduled maintenance. BitMEX recently published an update detailing two DDoS attacks.

Source: Coin Metrics Market Data Feed

Conclusion

After a crazy week, the initial data from the aftermath is somewhat reassuring. Most of the sell-off appears to have been driven by relatively short-term holders, and longer-term holders seem to be holding strong, at least for now. BTC has also entered a historically attractive price zone, with an MVRV below one.

But the markets are still volatile, and it is unclear what lies ahead. We will continue to track events very closely through this unprecedented time, and will provide updates and new analysis over the upcoming weeks.

CM Bletchley Indexes (CMBI) Insights

All of the CMBI and Bletchley Indexes had a week to forget after global financial markets fell sharply on fears as to the impact COVID-19 may have on the broader economy. All indexes lost over a third of their value, with the CMBI Bitcoin Index falling 36% and the CMBI Ethereum Index falling 42%. Whilst this was a market wide capitulation, the large-caps were the ‘least’ impacted in a shocking week, as evidenced by the Bletchley 10’s positive performance against BTC and the negative performance of all other indexes against BTC.

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • This is a special edition of State of the Network as a response to the recent market crash. Regular State of the Network sections including Network Data Summary and Market Data Insights will be back next week.
  • Coin Metrics is hiring! We recently opened up 4 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 41 – Using MVRV To Analyze Investor Behavior

Weekly Feature

Speculators vs Holders: Using MVRV To Analyze Investor Behavior

By Nate Maddrey and the Coin Metrics Team

In two previous issues of State of the Network (Primer on Cryptoasset Valuation Part 1 and Part 2) we conducted a comprehensive review of cryptoasset valuation research. In this issue we take a deep dive into one specific valuation metric: the market value to realized value (MVRV) ratio. 

MVRV is composed of two metrics: realized capitalization and market capitalization. In the following section we give an overview of how realized capitalization is calculated, as a prerequisite to an explanation of MVRV.

All of the data used in this report including realized cap and MVRV is available as part of Coin Metrics Network Data Pro. More information is available on our new website.

Realized Capitalization Overview

Realized capitalization is a metric created by Coin Metrics that is calculated by valuing each unit of supply at the price it last moved on-chain (i.e. the last time it was transacted). This is in contrast to traditional market capitalization which values each unit of supply uniformly at the current market price. 

For example, if Bitcoin’s (BTC’s) current price was $10,000, traditional market cap would value each coin equally at $10,000. If the current total BTC supply was 18 million, this would result in a total market cap of $180,000,000,000 (18 million multiplied by $10,000). 

Realized cap, on the other hand, values each coin at the time it was last moved on-chain. So if a coin was last transacted when BTC was $2,500, that particular coin would be priced at $2,500 instead of the current market price. The realized cap is the total sum of all coins priced this way. 

Realized cap can be thought of as an estimation of the aggregate cost basis of a cryptoasset.  This provides a valuable view into investor behavior that is not really possible with most traditional, non-crypto assets.

It’s important to note that this is just an estimate and not an exact measurement of investor cost basis. Realized cap measures the value of coins the last time they were transacted, not necessarily the last time they were traded or exchanged. But since cryptoassets are mostly used for investing/trading and not for payments (at least for now), realized cap can be used as a generalized proxy for cost basis. 

Realized cap also accounts for lost coins better than market cap. For example, if 100 BTC were last moved in 2011 when BTC price was $1, there is a decent chance that those particular BTC are permanently lost (see State of the Network Issue 26 for our analysis on the amount of BTC that has been permanently lost).  Realized cap would value these coins at a total of $100 (100 BTC multiplied by $1), while market cap would value them at current market prices.

Market Value to Realized Value Overview

MVRV is the ratio of a cryptoasset’s market cap (aka market value) to realized cap (aka realized value). It can be used to help gauge cryptoasset market tops and bottoms, and also to gain more insight into a cryptoasset’s investor behavior.

One way to view MVRV is to think of it as a comparison between speculator and holder valuation of a cryptoasset. Under this interpretation, market cap can be thought of as an estimation of speculators’ current market value (assuming sudden market cap changes are mostly driven by speculation). Realized cap, on the other hand, is a gauge of holders’ market valuation, since it reflects prices at time of last transaction and is not as affected by sudden price swings. 

An MVRV of one is therefore an important cutoff. An MVRV above one signals that speculators have a higher average market valuation than holders. An MVRV below one, on the other hand, signals that holders have (or had) a higher market valuation than current speculators. Holders are tested when MVRV swings below one, as it becomes less and less likely they will be able to immediately sell their holdings at a profit.

MVRV has historically been a good indicator of market tops and bottoms, at least for BTC. Peaks in MVRV have typically indicated that the market is at a top, while lows have occurred during times when a the market is at a bottom or in an accumulation period. 

But up until this point, most of the research around MVRV has focused on BTC and not other cryptoassets. BTC’s MVRV has mostly stayed above one, with a few accumulation periods where it briefly dropped below. However this is not the case for all cryptoassets. 

In the following section we analyze the MVRV ratio for a variety of cryptoassets, and explore what differing MVRV patterns tell us about each specific asset.  

Market Value to Realized Value Analysis

Historically, peaks in BTC MVRV have coincided with peaks in BTC price. MVRV spiked above 5.5 in Apr. 2013 and Nov. 2013, and above 4.5 in Dec. 2017, all three of which were local market tops. 

Conversely, there have been three periods since 2011 where BTC MVRV dipped below one: Sept. – Dec. 2011, Jan. – Oct 2015, and Nov. 2018 – Apr. 2019. In hindsight, all three of these periods have been some of the best times to accumulate BTC.

BTC MVRV shows relatively healthy patterns of growth followed by accumulation periods. MVRV has rebounded back above one after all three times it dropped below, which shows that there has been long term support by holders that has balanced out cycles of speculation. 

Source: Coin Metrics Network Data Pro

In its first few years of existence Ethereum (ETH) MVRV was well above one, which signaled a relatively speculative period. Fueled by the ICO craze, ETH MVRV spiked to 2.94 in March 2017 and 3.14 in June 2017 during local market tops. But it has declined since then, and has not topped 3.0 since the mid-2017 peak. 

ETH’s MVRV reached its lowest point in December 2018, when it dipped below 0.3. It then swung upward in early 2019 and again in early 2020, which signals that ETH potentially also has a base of holders who help support speculative growth spurts. ETH’s recent MVRV spikes have not been as high as BTC’s though, which suggests its in a slightly more precarious position. 

Source: Coin Metrics Network Data Pro

Similar to ETH, Ripple (XRP) initially had an MVRV well above one, which signaled that it was a relatively speculative asset. But in mid-2018 XRP’s MVRV abruptly dropped below one, and has not broken back above since. XRP’s MVRV inability to rebound back above one signals that speculative enthusiasm for XRP may be waning. If that is the case, holders are may increasingly be underwater.

Source: Coin Metrics Network Data Pro

Tezos (XTZ) MVRV shows an opposite pattern to XRP. XTZ MVRV remained below one for most of its history, and then suddenly shot above one in early 2020. This signals that XTZ likely had strong holder support for most of its early years. But its future is less clear – the sudden rise in MVRV could potentially signal that XTZ is turning the corner to an upswing, and/or that it is entering a period of high speculation.

Source: Coin Metrics Network Data Pro

Bitcoin SV (BSV) MVRV has been above one since its inception, which likely signals a relatively speculative market. Although BSV MVRV has fluctuated up and down, the level of holder support at MVRV of below one remains to be seen.

Source: Coin Metrics Network Data Pro

Conclusion

Cryptoasset valuation is still a burgeoning field, but there has already been a lot of interesting research about novel crypto-specific indicators. MVRV is a powerful metric that uses on-chain data to gauge market tops and bottoms, as well as provide information into the overall health of a cryptoasset. But it’s also important to look at other on-chain data and fundamental indicators in addition to MVRV to get a full picture of whether a cryptoasset is undervalued, or just underwater. We will continue to track MVRV across all major cryptoassets and provide updates through the latest market volatility.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Despite the market slide, usage metrics for most of the major cryptoassets were up this past week. BTC active addresses grew 5.3% week-over-week, while Litecoin (LTC), XRP, and Bitcoin Cash (BCH) active addresses all increased by 17% or more.  ETH active addresses saw a slight decline, however, dropping 4.9%.

ETH fees also dropped more than the other assets in our sample, declining by over 15%. However, it’s important to note that ETH still had an average of $96.2K of daily fees over the last week, while XRP, LTC, and BCH all had an average of less than $1K.

Network Highlights

We recently partnered with Blocknative to provide data for their research on transaction growth. The following excerpt and chart, taken from their report, shows aggregate transactions from 2009 until 2019:

“Significantly, we crossed the 1 billion aggregate transactions per year threshold in 2019. In fact, more than 37% (>1.1 billion) of all blockchain transactions in history occurred in 2019.”

Source: When One Billion Ethereum Transactions?

Over the last 180 days, Paxos (PAX) has outgrown Omni-issued Tether (USDT), Ethereum-issued Tether (USDT_ETH), USD Coin (USDC) and TrueUSD (TUSD) in terms of daily transactions count. PAX has grown about 545% over the period, while USDT and USDT_ETH transactions count has actually slightly declined. The following charts show percent growth smoothed using a seven day rolling average.

Source: Coin Metrics Network Data Pro

USDC, however, led the way in terms of adjusted transfer value growth. USDC grew by about 80%, while PAX was about even. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Most cryptoassets experienced downturns this week as broader financial markets steeply declined in response to the coronavirus and crude oil price war. 

In a previous State of the Network, we showed quite strong evidence that BTC responded efficiently as military tensions escalated between the United States and Iran earlier this year. In the past week, BTC has been highly correlated with global equities with a near identical reaction to the Fed’s surprise 50 basis point interest rate cut and a coordinated sell-off on Sunday as futures markets opened. While events similar to this have happened in BTC’s history (such as during the Cypriot banking crisis, Greek default fears, and the initial passing of the Brexit referendum), the increased frequency of such events indicate that the “uncorrelated asset class” part of BTC’s narrative may no longer ring true in the future. 

Source: Coin Metrics Reference Rates

While gold has seen brief moments of weakness due to increased liquidity needs, it has nonetheless continued to serve as a relative safe haven asset with prices at seven year highs. BTC’s poor performance, in contrast, has raised legitimate questions about its ability to serve as a safe haven. 

In order to provide some historical benchmarks, we investigated the performance of BTC during acute moves in various risk-off indicators. 

S&P 500

To start, we investigated the S&P 500. Equities are typically considered to be risk assets and, as a key benchmark for equities, the S&P 500 typically falls during risk off environments. We selected the 20 worst days for the S&P 500 since the beginning of BTC’s price availability (7/18/10). 

During these 20 days, the S&P 500 had an average return of -3.77% and a median return of -3.49%. The average return of BTC during these 20 days was -0.78%, with a median return of -0.40%. 

Source: Coin Metrics Reference Rates

VIX

We also took a look at the VIX, a volatility index commonly referred to as the “Fear Index”. Volatility increases during periods of uncertainty, driving this index higher. We reviewed the 20 largest single day gains in the VIX since the beginning of BTC’s price availability.

During these 20 days, the VIX had an average gain of 44.6% and a median increase of 42.6%. The average return of BTC during these 20 days was 0.1%, with a median return of 0.5%. 

Source: Coin Metrics Reference Rates

10Y Treasury Rates

During risk off environments, investors typically purchase treasuries (which are considered safe haven assets), funded by sales of risk assets such as equities. We looked at 10-Year Treasury Constant Maturity Rates, selecting the 20 largest rate drops since the beginning of BTC’s price availability.

During these 20 days, the 10 year treasury rate had an average decline of 0.1560 percentage points and a median rate decline of 0.1600 percentage points.

The average return of BTC during these 20 days was 2.8%, with a median return of 3.1%. 

Source: Coin Metrics Reference Rates

As can be seen from the summary table below, BTC’s behavior relative to other risk indicators is inconclusive. At a superficial level, BTC appears to fall less than the S&P 500, but it also gains significantly less than the VIX. BTC’s average gains during instances where 10 year treasury rates fell significantly is interesting and an opportunity for the kind of future research required to provide a more comprehensive and thorough picture of BTC’s performance during times of market stress. 

Summary of Bitcoin’s Performance during days of acute market stress

Despite the performance during certain days of market stress illustrated above, historical correlations between BTC and financial assets have remained close to zero. Recent events, however, suggest a stronger relationship between BTC and events that affect broader financial markets. In light of recent data, BTC’s lack of correlation may be explained by its lack of maturity as an asset class rather than an inherent property. 

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes fell again this week as the cryptoasset market experienced volatility and poor performance. 

After starting the week strongly with most indexes up 10% on Friday, sentiment changed quickly through the weekend. The CMBI Ethereum Index was the best performer of the week, down only 0.7% for the week but returning 1.6% against BTC. Small-cap cryptoassets performed the best this week with the Bletchley 40 only experiencing a 1.5% drawdown. 

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 4 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 40 – Cryptoasset Valuation Research Primer, Part 2

Weekly Feature

Cryptoasset Valuation Research Primer, Part 2

By Kevin Lu and the Coin Metrics Team

In a previous State of the Network, we published the first part of our cryptoasset valuation research primer focused on summarizing and synthesizing this emergent field in the literature. 

Our introduction in the first part describes our approach: 

We conducted a comprehensive literature review to identify all major facets of cryptoasset valuation research that has been conducted so far. All methods were considered, from theoretical valuation frameworks, to empirical valuation models, to novel indicators that have application to valuation. 

In short, we are interested in all research that can be used to understand the current value of cryptoassets, estimate the value of cryptoassets, or predict future values of cryptoassets. All publication mediums are considered, regardless of pedigree, from forum postings to academic journals. The most salient articles from both academic and industry researchers are included. 

In the second part to our cryptoasset valuation primer, we survey five additional facets of the literature: fundamental ratios, UTXO age analysis, realized capitalization-based analysis, factor investing, and social media-based analysis. 

Fundamental Ratios 

The use of fundamental ratios is one of the most widely used approaches to cryptoasset valuation. Taking inspiration from the field of fundamental equity research (particularly ratios such as the price-earnings ratio), fundamental ratios are frequently used to determine periods of overvaluation and undervaluation. 

Woo (2017) was the first to make the connection that fundamental ratios could be applied to cryptoassets by introducing the network value to transactions (NVT) ratio, calculated as a cryptoasset’s market capitalization divided by its daily value transacted over the network. The logic behind this approach is that daily transaction value represents the usage and utility of a cryptoasset. High values of the NVT ratio have reliably detected bubbles and low values have indicated attractive entry points in the past. 

Kalichkin (2018a) extends the idea behind the NVT ratio by introducing additional smoothing to correct for certain shortcomings in the original formulation that prevent it from being used as a real-time trading indicator. Kalichkin’s version of NVT is often referred to as NVT Signal. 

Source: Coin Metrics Network Data Pro

Franek (2018) introduces a new ratio, based on a valuation derived from Metcalfe’s Law called the network value to Metcalfe ratio, which Kalichkin (2018b) extends by empirically testing on other similar laws. 

Arun (2018) also explores alternatives methods of smoothing and more precise estimates of daily transaction value. Combining ideas from both Metcalfe’s Law and the NVT ratio, the article introduces a network value to transactions to growth (NVTG) ratio. As a critical input to the NVT ratio, Coin Metrics (2018a) more precisely estimates transaction value by removing change outputs and non-economic transfers.

Bitcoin network momentum, introduced in Swift (2018), does not use a fundamental ratio, but instead introduces daily transaction value denominated in native units as a leading indicator for prices. 

Several other ratios have been proposed that are derived from miner revenue which represents the dollar value of capital that secures a network and a cryptoasset’s intrinsic value. Miners are also a consistent and significant source of selling pressure. For these reasons, Leibowitz (2018) defines a fee ratio multiple which provides a measure of how much of a cryptoassets security spend is dependent on block rewards versus transaction fees. And cryptopoiesis (2019) defines the Puell ratio as daily issuance divided by a 365 period moving average of daily issuance. 

Research using fundamental ratios touches upon many facets of the literature. Several additional fundamental ratios leveraging other inputs have been introduced in the fields of UTXO age analysis and realized capitalization ratio, including the the liveliness ratio, market capitalization to realized capitalization (MVRV) ratio, the spent output profit (SOPR) ratio, and the realized capitalization to transaction value (RVT) ratio and others. These areas of the literature and their associated ratios are discussed in the following sections. 

Fundamental ratios are perhaps the most developed thread in the literature due to their straightforward interpretation and application to market timing. Still, more work can be done in this area to address certain shortcomings. The most salient criticism points to reduced out-of-sample accuracy in predictions for some ratios such as the NVT ratio and the increasing tendency for more transactions to occur off-chain, either on second layer networks or within an internal ledger of an exchange or custodian. Furthermore, the extremely strong impact that the  bubble-and-crash cycle has on price means that any transformation (such as using ratios) that de-trends price tends to show excellent within-sample predictions but might not necessarily generalize well out-of-sample. 

UTXO Age Analysis 

Unspent transaction output (UTXO) age analysis is an area of the literature that studies the supply side of a cryptoasset by examining the behavior of holders. UTXO refers to the output of a transaction that a user holds and is able to spend by serving as inputs into future transactions. This accounting model is used by Bitcoin (BTC) and several other UTXO-based chains. Although the naming of this area of the literature makes specific reference to UTXOs, several of the concepts developed here have been successfully adapted to account-based chains, such as Ethereum. 

The earliest known contribution to this field was in ByteCoin (2011) where the term “Bitcoin days destroyed” was first defined as an alternative measure to transaction value. Bitcoin days destroyed is calculated as the number of BTC transacted over a period of time multiplied by the number of days since those BTC were last transacted. This gives a higher weight to coins that have not been spent in a long time, and less weight to coins spent more recently. For example, a coin that had not been transacted in 100 days is weighted 100x more than a coin that had been transacted 1 day ago. This fundamental insight, that inferences can be made by analyzing the age of last use for each coin, set the foundation for subsequent research. 

The following chart shows BTC transfer value weighted by days destroyed, smoothed using a seven day rolling average. 

Source: Coin Metrics Network Data Pro

The next significant contribution was in jratcliff63367 (2014), which partitioned the total supply of BTC into various bands based on the age of last use. In subsequent years, industry terminology has converged on the terms active supply or more informally, “HODL waves.”

The same idea was revisited several years later in Bansal (2018) which was instrumental in introducing active supply to a broader audience. The article was the first to draw inferences from active supply with respect to understanding and predicting market cycles and with applications to trading. 

Blummer (2018) defines liveliness as, using terminology introduced above, “the Bitcoin days destroyed divided by the total Bitcoin days that currently exist.” Liveliness provides insight into investor behavior by quantifying the behavior of long-term and short-term holders. 

Hauge (2019) presents several extensions to Bitcoin days destroyed, including adjusted binary Bitcoin days destroyed, value of coins destroyed, and reserve risk, all with applications to market timing. 

The unifying theory behind this approach to valuing cryptoassets is that different cohorts of holders may have differing motivations, risk tolerances, informational advantages, and sentiment depending on their holding time preferences. For instance, long-term holders hold a disproportionately large amount of the supply for many cryptoassets, and their behavior has large implications for price discovery. In our opinion, this area of the literature remains one of the promising areas in which more foundational discoveries can be found. 

Realized Capitalization 

Realized capitalization represents a novel, cryptoasset-specific approach to valuation that has significantly advanced the field of on-chain analysis. Unlike market capitalization, which values each coin at its current price, realized capitalization values each coin at the time of its last on-chain movement. For example, if 10 BTC were last moved when BTC price was $1,000, those 10 BTC would collectively be valued at $10,000 (10 x $1,000). If 5 different BTC were last moved when the price was $10,000, those 5 BTC would be valued at $50,000 (5 x $10,000).

Under an additional assumption that each on-chain movement represents a transfer of ownership between a willing buyer and willing seller, such that the price at the time of the transfer represents the cost basis of the buyer, realized capitalization can also be interpreted as the aggregate cost basis of all holders. 

While UTXO age analysis is concerned about the age at which a coin was moved on-chain, realized capitazalition-based analysis is concerned with the price at which a coin was last moved on-chain.

The core ideas were introduced in Coin Metrics (2018b) which provides a method of calculating realized capitalization for UTXO-based blockchains and account-based blockchains. The market capitalization to realized capitalization (MVRV) ratio is also presented in this article and is further explored as an indicator to identify periods of overvaluation and undervaluation in Mahmudov and Puell (2018)Awe & Wonder (2018) extends the MVRV ratio by applying a z-score transformation which allows it to serve as a more reliable trading indicator. 

Source: Coin Metrics Network Data Pro

Checkmate (2019) formulates the realized capitalization to transaction value (RVT) ratio which uses the same fundamental principles behind the NVT ratio but uses realized capitalization instead of market capitalization in the numerator of the ratio. 

Carter (2018) introduces thermo capitalization, a closely related concept of realized capitalization, which values each coin at the price at which the coin was originally mined. Under the assumption that miners operate at a long-term profitability equilibrium of barely above breakeven, thermo capitalization represents the accumulated security spend of the network. 

Puell (2019) introduces delta capitalization, a related concept that is calculated as the realized capitalization minus average capitalization (a cumulative, trailing moving average of market capitalization). A series of trading signals based on this indicator are explored with good within-sample performance. 

Similarly, Demeester, Blummer, and Lescrauwaet (2019) develops a measure to quantify the unrealized profit or loss of investors by calculating the market capitalization minus realized capitalization. Using liveliness, the article defines an indicator representing the change in long-term investor behavior. Shirakashi (2019) originated the spent output profit (SOPR) ratio by quantifying realized gains and losses and uses the ratio to predict local bottoms and tops. 

The realized capitalization line of analysis represents a truly cryptoasset-specific approach to valuation due to our ability to derive insights from the blockchain ledger. Being able to estimate the cost basis for all individual investors is a profound discovery (that is impossible to replicate in traditional financial assets) with serious applications to measuring investor sentiment and advancing the field of behavioral economics. Actively managed trading strategies that leverage deeply-rooted human cognitive biases and derived from realized capitalization insights are likely to be effective. 

Factor Investing 

Factor investing makes reference to models which identify specific characteristics of cryptoassets to explain returns. It further extends a very developed area of the literature in traditional financial assets, founded on Fama and French’s seminal work which identified three factors (market risk, size, and value) that explain U.S. equity returns. Since then, researchers have significantly expanded the field of factor investing by identifying hundreds of factors, not only in U.S. equities, but  in other geographies and asset classes. Cryptoassets are a natural next candidate of study. 

While other articles previously conducted cross-sectional studies to identify characteristics relevant to cryptoasset values, the first serious study using a traditional factor investing methodology was conducted in Hubrich (2017). It is the first known application of momentum, value, and carry factors to cryptoassets. The paper introduces innovative interpretations of value as the ratio of market value to on-chain transaction volume, and carry as the rate of supply issuance. The evidence suggests cryptoasset factor investing can earn excess returns. 

Liu and Tsyvinski (2018) significantly adds to the factor investing literature. It tests a wide number of traditional, macroeconomic, and cryptoasset-specific factors and finds evidence that a momentum factor and factors based on investor attention consistently explain cryptoasset returns but also finds a lack of predictive power for other factors. Kakushadze (2018) confirms the strong finding of a significant momentum effect and also finds lack of predictive power for a liquidity factor. Liu, Tsyvinski, and Wu (2019) extends the work on previously identified factors by introducing discussion regarding portfolio construction. 

Additional progress on this thread of the literature is dependent on the evolution of cryptoasset markets. Factor investing is concerned with evaluating large numbers of assets to determine characteristics that explain returns. Additionally, it seeks to construct portfolios consisting of many assets with exposure to certain factors. Therefore, the degree to which investors desire exposure and can obtain exposure to assets in the long-tail is important. The ability for researchers and data providers to identify conceptually consistent network data across assets, regardless of the underlying blockchain architecture, is also a prerequisite for further advances. 

Social Media 

The study of the relationship between the price of cryptoassets and social media-related data has a long history in the literature. Cryptoasset fundamentals are still only beginning to be understood (and the short history available to us shows that prices can deviate from fundamentals by a wide margin and for sustained periods), so quantifying investor attention is an active area of research. 

Kristoufek (2013) was the first article to use search query volume on Google and Wikipedia to serve as proxies for investor attention and to perform a study of its correlation to BTC’s price as well as tests on causation and co-integration. Garcia, Tessone, Mavrodiev, and Perony (2014) uses a broader set of data beyond search volume which includes Twitter and Facebook activity as well as data outside of social media. Two positive feedback loops are identified: one driven by word of mouth, and the other by new BTC adopters. 

Using a very similar methodology and an even broader set of data that includes several measures of on-chain activity, Georgoula, Pournarakis, Bilanakos, Sotiropoulos, and Giaglis (2015)finds that Twitter sentiment, among other indicators, has a positive short-run impact on BTC prices. A related study in Polasik, Piotrowska, Wisniewski, Kotkowski, and Lightfoot (2014) finds that BTC price returns can be explained by newspaper mentions, among other indicators. Mai, Shan, Bai, Wang, and Chiang (2018) present an empirical study using more updated data and concludes that social media sentiment is an important predictor for BTC prices. 

Conclusion 

Conventional wisdom states that cryptoassets are difficult to value because they lack a firm anchor to existing methods of asset valuation. But a close examination of the current state of cryptoasset valuation research reveals that this statement is not necessarily true. 

Over the past 10 years, existing concepts from classical economics, monetary economics, discounted cash flow analysis, fundamental equity research, and other fields have been successfully adapted to valuing cryptoassets. 

Simultaneously, several researchers have made noteworthy progress on cryptoasset-specific approaches to valuation which leverage on-chain data. An open ledger containing a historical record of all transactions allows for study of investor behavior, with unprecedented clarity compared to traditional financial assets. Foundational concepts upon which a formal discipline of cryptoasset valuation can be built have been established and many additional concepts likely remain undiscovered for the moment. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

The major cryptoassets had a big drop-off this past week amid a general market downturn. As fear continues to build about the spread of coronavirus, Bitcoin (BTC) dropped back below $9,000 and the equities market had its worst week since 2008.

Other cryptoassets fell even more than BTC. Ethereum (ETH) market cap dropped 12.7% week over week. Ripple (XRP), Litecoin (LTC), and Bitcoin Cash (BCH) all dropped between 14% and 16%. ETH and other smaller assets outpaced BTC in the recent run past $10,000, and it appears they may also be outpacing BTC on the way down.

Network Highlights

The percent of BTC untouched in at least two years is approaching levels unseen since mid-2017. As of March 1st, about 42% of all BTC has not been moved on-chain (i.e. transacted) for at least two years. The amount of BTC untouched in more than two years has not eclipsed 42% since July, 2017.  

Source: Coin Metrics Network Data Pro

There was not a large spike in transfer value days destroyed prior to the recent BTC price slide under $9,000. Although there were a few peaks in early February on the 3rd and 7th, there have not been any abnormally large spikes since. 

As covered in the Weekly Feature, BTC transfer value days destroyed is defined as BTC transfer value multiplied by the number of days since those BTC were last transacted. This gives a larger weight to transfers that involve coins that have not been moved in a long time. Spikes in transfer value days destroyed signal that long-dormant coins have been transferred, which could potentially precede sell-offs.

Source: Coin Metrics Network Data Pro

Market Data Insights

Cryptoassets sold off in concert with risk assets over the past week due primarily to the realization of the economic cost required to contain the coronavirus as the number of confirmed cases accelerate outside of China. During times when need for liquidity is high, reputed safe haven assets such as BTC and gold can be sold since liabilities can typically only be paid in fiat currency. Liabilities can take the form of margin calls in its most immediate form but also include debt service obligations like interest and principal payments. 

Source: Coin Metrics Reference Rates

Interestingly, BTC has seen a gain, along with global equities, after comments from the Bank of Japan (which held an emergency meeting on Monday) stating that they would take steps to stabilize markets. Such events should not be examined too closely in isolation due to the random walk that asset prices can take, but it continues to add to the body of evidence that BTC and the broader cryptoasset market do react to events beyond the immediate industry. 

Despite the sharp declines in cryptoassets, forced liquidations on BitMEX and other futures exchanges remain modest in sharp contrast to the pattern seen last year. Perhaps more dispersed volume across derivatives exchanges is lessening the impact of any one exchange. 

Realized volatility still remains moderate for BTC but a firm trend of increasing volatility for almost other assets remains. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

The best performing CMBI  index this week was the CMBI Bitcoin Index, despite its 14% drop. This is evidenced by the negative performance of all other CMBI indexes when denominated in BTC value.

After its record run of 9 consecutive weeks of positive performance, the CMBI Ethereum Index was one of the worst performing indexes, falling over 20% during the week. Of the multi-asset indexes it was the Bletchley 20 (mid-caps) that were most impacted experiencing a 20% fall.

Source: Coin Metrics CMBI Index

Despite the poor weekly performance, the CMBI Ethereum Index was by far the best performer in February, returning 25% for the month whilst most other indexes experienced between -5% and +5% returns. The CMBI Bitcoin Index was the worst performer of the month falling 6%.

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 4 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 39 – In Search of an Elusive BCH Jackpot

Weekly Feature

The Miner’s Dilemma: In Search of an Elusive BCH Jackpot

By Antoine Le Calvez and the Coin Metrics Team

“I thought for a long time whether to write here. And now that I am doing it, I doubt whether I am doing the right thing. Imagine that there is a casino with a jackpot of $500k. To hit it, you need to bet about $15k and the probability that the bet will payout is about 60%. The problem is that there are several more people that know about this jackpot for sure. What would you do in a similar situation?”

On November 20th 2017, a russian Bitcointalk user ponders over an interesting opportunity that presents itself to him. To understand it, we must go back in time.

Several weeks earlier, two crucial events unfolded: on August 1st, Bitcoin Cash forked away from Bitcoin. Then, on August 24th, Bitcoin activated its most important upgrade in years: SegWit (segregated witness).

The Bitcoin Cash fork created two assets that shared practically everything. Importantly for this story, both networks support special types of addresses, P2SH (pay-to-script hash), that start with a ‘3’. These addresses enable usage of complex scripts like multisignature schemes. The script associated with a P2SH address is only known when the address gets “spent from”: someone sending BTC or BCH to a never-spent-from P2SH address cannot know what script it uses.

SegWit, among many other changes, added a special type of P2SH address: nested SegWit. They look like normal P2SH addresses, but their spending script uses SegWit. It offered an easy and backward compatible way to onboard users to SegWit.

Over time, users have been mistakenly sending BCH to nested SegWit addresses. As Bitcoin Cash doesn’t implement SegWit, these addresses’ scripts fallback to looking like anyone-can-spend addresses (which do not require a signature; all you need is the knowledge of the script). This misplaced BCH is therefore effectively a jackpot waiting for whoever can get there first. 

This figure only gives a minimum estimate of how many BCH have been mistakenly lost this way. We can only detect whether an address uses nested SegWit when the script the address uses is revealed. As time goes on, more and more addresses can be detected, which will inflate this figure.

There is one slight caveat though: only miners can access this jackpot. Transactions have to obey consensus rules (no double spending, etc.) but there’s another set of rules they have to obey in order to be relayed by nodes: standardness rules, which were implemented to avoid denial-of-service attacks using large or very complex transactions. Bitcoin has a small number of standard scripts that are relayed from node to node. Non-standard scripts are accepted as part of mined blocks, but these non-standard scripts are not relayed from node to node. 

Transactions spending from a nested SegWit address on Bitcoin Cash break one of these standardness rules (the cleanstack rule, to be precise) and therefore will not be relayed; they can only be mined if included directly by a miner. So miners, or a user in direct contact with a miner,  can spend from nested SegWit addresses on Bitcoin Cash, while normal users cannot. 

With this knowledge, we can decipher the opportunity that presented itself to our Russian Bitcointalk user:

  • $500k jackpot: at the time the user wrote his post, there were slightly more than 400 BCH (worth around $500k at the time) sent to nested SegWit addresses on Bitcoin Cash that could only be claimed by miners.
  • $15k bet: this is what it would cost to rent 1/144th of BCH’s hashrate for a day.
  • 60% payout chance: a 1/144th miner has a ~63% chance of mining a block in a single day.

If only he could mine a block, he could claim the jackpot for himself: 

“I need to mine a block. But all the pools are in China and I have no friends among admins.”

Over time, more than 19,000 BCH have been sent to nested SegWit addresses. In this feature, we will look at the fate of these mistakenly lost BCH.

The Jackpot is Born

On September 10th 2017, Reddit user /u/btctroubadour noticed a worrying pattern of events: many Trezor users were sending BCH to nested SegWit addresses. He recommended setting up a miner-run recovery service that would gather this lost BCH and give them back to users (minus a finder’s fee for the pools’ trouble). As per usual with constructive contributions on the internet, the discussion quickly degenerated into endless debates and attacks and nothing came out of it.

However, several people took notice and started thinking about this issue. Furthermore, as time went on, the size of the bounty created by this issue kept growing.

Around this time, our Russian Bitcointalk user probably took notice of the issue and started searching for a miner amenable to mining transactions breaking the standardness rule which prevents regular users from claiming these coins.

One week after, having found no existing mining pool willing to include his transactions, he posts on Bitcointalk, wondering if he could create a temporary pool on Bitcoin Cash, just to mine a single block.

On November 14th 2017, I tweeted about this issue, giving the first public estimate of the bounty available at the time: 478 BCH (worth $644k at the time).

Two days later, on the 16th, the first ever recovery took place: 100.7 BCH mistakenly sent to a nested SegWit address were recovered by BTC.com.

A White Hat Appears

On November 21st 2017 the hopes and dreams of our Russian Bitcointalk user were crushed: an anonymous Reddit user (/u/bchsegwitrecover) recovered 493.5 BCH ($600k at the time) and offered to give it back to affected users after charging a 30% finder’s fee. The catch is that users had to submit claims before December 6th 2017.

The block that included this recovery transaction included a second recovery operation of 12.64 BCH sent to a nested SegWit address. However, this recovery was special because the script needed to recover the BCH was never made public on the Bitcoin chain. Therefore it must have been communicated to the miner directly, to avoid having the lost BCH “claimed” by someone that wouldn’t give it back.

These 12.64 BCH were sent to the same address that recovered 100.7 BCH earlier, which is possibly related to BitGo.

After November 28th, /u/bchsegwitrecover decided to forego his 30% finders fee and reimburse the fees already collected. 

By tracing payments initiated by the address that received the recovered funds, we estimate that /u/bchsegwitrecover sent back lost BCH to 7 users for a total of 75.59 BCH (including reimbursed finder’s fee). Interestingly, one user apparently managed to negotiate the fee down to 15% (however, it got reimbursed like all other users).

The fate of the BCH unclaimed by the deadline is murkier as the funds have gone through peeling chains (where a large amount is peeled off in many smaller denominations over many transactions) making tracing what happened to the funds more difficult.

Two days after /u/bchsegwitrecover’s announcement, BTC.com launched a recovery service, charging a 10% recovery fee, fulfilling /u/btctroubadour’s vision from months earlier.

BTC.com’s Recovery Service

The introduction of BTC.com’s recovery service started a new era for these lost BCH. Now, public mining pools would mine transactions recovering mistakenly lost BCH.

Using BTC.com’s tagging of BCH miners, we tracked how much BCH each mining pool recovered:

Focusing on BTC.com’s recovery transactions, we can uncover interesting things. Its nominal 10% finders fee was seemingly always sent to the same address, which allows us to determine the revenue the pool got from it: 368.03 BCH.

Astute readers will have noticed that their revenue of 368.03 BCH and their recovered amount of 5,779.30 BCH don’t align with their supposed 10% finders fee. We found 12 transactions for which a lower finder’s fee was charged by BTC.com, of which 5 had a fixed fee of 10 BCH for amounts larger than 100 BCH. This indicates that at some point in time, BTC.com decided to cap their finder’s fee to 10 BCH.

BCH Hard Forks

Bitcoin Cash has a policy of bi-annual hard forks, on May 15th and November 15th of each year. 

Two of these hard forks are relevant for SegWit recoveries:

One consequence is that during the 6 months period during which recovering SegWit funds was impossible, a large amount of lost BCH accumulated and became spendable on the May 15th fork, as is visible on this chart.

This accumulation of anyone-can-spend money (around 4k BCH, or $1.6M at the time) created a bounty that attracted nefarious interests.

As analyzed by BitMEX research, several issues compounded after the hard fork which caused various chain splits. One of these issues made miners produce empty blocks. Right after this bug was fixed, the “fake unknown” miner claimed the nested SegWit BCH bounty for himself. According to an account of the incident by Chinese user “BCH Bruce Lee” on WeChat

“After discovering this situation, the big BCH miners urgently allocated a large amount of hashpower from BTC to mine BCH, actively initiated the chain reorganization of the two blocks, voided the “fake unknown” mining pool transaction, and sent back the mistakenly lost BCHs to their original owner.”

The “fake unknown” block claiming the mistakenly lost BCH was indeed orphaned by other miners.

Mining pools orphaning an otherwise valid block on purpose is a very rare event. The fact that it happened to avoid many innocent users losing access to their lost BCH makes it unique. This incident can be contrasted with another event that happened one week earlier on BTC: Binance lost 7,000 BTC from a hack and considered colluding with miners to reorg the thief’s transactions out. However, this plan was quickly abandoned.

In a later block, BTC.TOP recovered 3.8k BCH from nested SegWit addresses using a novel technique. Instead of having to wait for claimants to come forward and having to validate that they controlled the address that received the lost coins, they used the information present in the nested SegWit scripts to craft a non-SegWit address that only the holder of the original address could spend. This way, they can give users control over their lost BCH without having to get in contact with them.

However, BTC.TOP didn’t recover all the claimable BCH post-fork; 10 blocks after they recovered 3.8k BCH, the “fake unknown” miner claimed 216 mistakenly lost BCH, whose fate is unknown.

Conclusion

Using all the information above, we can retrace with some certainty the fate of half of the mistakenly lost BCH:

Publicly identified miners are a paragon of virtue, returning the majority of the BCH they recovered to their rightful owners. However, the fate of half of the lost coins is still undetermined. 

They have been “recovered” in blocks that haven’t been associated with any known pool. This “unknown” mining entity has been diligently recovering most of the lost BCH (except for the post-May 15th bounty) since mid-2018.

And so the search continues. As is often the case with blockchain archaeology, solving one problem leads to others. No matter where it may lead, we will continue to follow this story, and look forward to unraveling more blockchain mysteries.  

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

After several weeks of positive growth, the major cryptoassets cooled off a little this past week. Bitcoin (BTC) and Ethereum (ETH) both saw declines in usage, and a drop in most economic metrics including daily fees and adjusted transfer value.

However, mining and security measures for both cryptoassets continued to show positive growth over the last 7 days. BTC and ETH estimated hash rate increased by 4.8% and 3.7% week-over-week, respectively. 

Network Highlights

ETH has had a strong month of market cap growth. Looking at on-chain data, it has also outperformed in several key network metrics.

Over the past 30 days, ETH active addresses have grown 41% (using a seven-day rolling average). Comparatively BTC active addresses have grown by 1%. 

Source: Coin Metrics Network Data Pro

ETH has also outpaced most other major cryptoassets in terms of adjusted transfer value growth. Over the last 30 days, ETH’s adjusted transfer value has grown by 132% (using a seven-day rolling average) compared to 11% for BTC.

Source: Coin Metrics Network Data Pro

Interestingly, ETH has also outperformed BTC in terms of the growth of transactions involving exchanges over the past 30 days.

Source: Coin Metrics Network Data Pro

Market Data Insights

The major cryptoassets remain in a narrow trading range over the past week with muted volatility. BTC’s annualized realized volatility measured over the past month and three months are around 50%, the low end of its recent historical range. 

Short-lived bouts of liquidations in the BTC futures market are causing sharp changes in price, both up and down, but have thus far not resulted in a sustained move. While large liquidations were a defining characteristic of 2019, so far in 2020 the impact of liquidations have been more moderate. 

Source: Coin Metrics Reference Rates

Escalation in the number of confirmed COVID-19 (coronavirus) cases and its ensuing economic impact present an additional opportunity to evaluate BTC’s safe haven characteristics. While market participants are quick to point out instances where BTC’s correlation with gold is high, such as during the summer in 2019, much less attention is paid to instances where BTC should react to safe haven capital flows but doesn’t. 

Events regarding the spread of COVID-19 in countries such as Korea and Italy are significant because of the sharp response in financial markets over the world. Equity markets have sold off while safe havens such as gold and U.S. treasuries have gained. BTC’s response is curiously absent — under a basic interpretation of the digital gold thesis, BTC’s price should have reacted positively but has instead declined. 

Source: Coin Metrics Reference Rates

In fact, the correlation between Bitcoin and gold measured over the past 30 days is currently negative, adding evidence to the thesis that BTC only reacts to certain types of events and not others. But past history has shown us that BTC shows qualities of a unique safe haven asset, able to hedge against true black swan-type events where centralized institutions fail or commit policy errors while simultaneously being unresponsive to normal macroeconomic surprises.

Under this lens, one explanation for BTC’s lack of reaction to COVID-19 events is that the virus represents more of a macroeconomic shock rather than an uncertain geopolitical  situation in which policy errors by centralized institutions are likely. And therefore perhaps BTC has characteristics of both risk-off and safe haven assets with a truly unique reaction function. 

CM Bletchley Indexes (CMBI) Insights

This week the majority of indexes remained relatively flat after mixed results across large, mid and small-cap cryptoassets. This week’s best performer was the CMBI Ethereum Index, which returned 7.5% for the week, and now has nine consecutive weeks of positive returns.

Of the multi-asset indexes, this is the first week of 2020 that the Bletchley 10 (large-cap) has performed the best among its market cap weighted peers. This is reflective of the relative strength of mid and small-cap assets in 2020, a trend that has not been as prevalent in crypto assets throughout 2019 and most of 2018.

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 4 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you’d like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics’ State of the Network: Issue 38

Weekly Feature

Analyzing Crypto Supply Distribution Patterns

By Nate Maddrey and the Coin Metrics Team

Those who control the wealth often control the power. But up until now, wealth distribution has been relatively hard to track. People often hide their wealth or obfuscate the true amount of assets that they hold. Cryptoassets take a big step towards making wealth distribution more transparent. 

Cryptoassets are the first asset class where it’s possible to track the full supply distribution throughout its history. Since every cryptoasset transaction is public and auditable, on-chain data can be used to calculate the balances held by every address at any given block. We can then look at the distribution of the size of the balances held by individual addresses to gain insights about the supply. 

However, supply distribution is not a perfect representation of wealth distribution. People often create multiple addresses, and it is difficult to figure out which addresses belong to a specific individual. Additionally, one address could be owned by many individuals, like an exchange cold wallet. To get an accurate cryptoasset wealth distribution you would need to know who controls each address. But transparent, auditable supply distribution gives a fascinating estimation of wealth distribution, and can also tell a lot about the usage patterns of a cryptoasset. 

For example, supply getting consistently more distributed could be a sign that the asset is getting real usage as a medium of exchange. Furthermore, analyzing sudden changes in the amount of supply held by addresses with large balances may lead to insights about selling and trading patterns. 

In this piece we explore the supply distributions of eight cryptoassets, and analyze what the changes in distribution tell us about each asset’s usage. 

Methodology

The charts throughout this piece show the percentage of supply held by addresses holding certain fractions of the total supply. 

We first looked at the balances held by each individual address. We then created groups of addresses holding different sized balances, ranging from relatively small to relatively large. To remain consistent across different cryptoassets, we grouped address balances by fractions of total supply, starting with addresses that hold at least one ten-billionth (1/10B) of total supply (0.0000000001%) and going up to addresses holding at least one one-thousandth (1/1K) of total supply (0.001%). For context, at time of writing, the total Bitcoin (BTC) supply is 18,214,117 so one ten-billionth of total BTC supply is 0.0018214117 BTC, equivalent to about $19. 

We then grouped these addresses into different discrete ranges based on balance size. We started with addresses that hold at least 1/10B but not more than 1/1B, then at least 1/1B but not more than 1/100M, etc., going up to addresses that hold 1/1K of total supply or greater (1/1K+). 

Finally, we calculated the sum of the supply held by all the addresses in each range, to get a percent of total supply held by each group of addresses. We include the cryptoasset’s price on the second y-axis axis (using log scale) to provide context about price changes during supply distribution movements.

It’s also important to note that there are some meaningful differences between the protocol design of different blockchains. For example, the supply of UTXO-based blockchains like Bitcoin becomes slightly more distributed over time as the UTXO set becomes more dispersed due to natural usage (new addresses are often created for each transaction on Bitcoin). This does not happen, however, in account-based chains like Ethereum where addresses are frequently re-used.

All of the data used in this piece is available as part of our Network Data Pro product. You can find more information about Coin Metrics Network Data Pro here

Supply Distributions

Bitcoin

BTC supply was initially held by a few individuals, but over time it has gradually been distributed to millions of different addresses.

The percentage of BTC supply held by large addresses (with a balance of at least 1/1K of total supply) peaked at about 33% in February 2011. As of February 2020, those addresses hold about 11% of total supply. Conversely, the percentage of supply held by smaller addresses with balances of 1/10M and lower has been steadily increasing since 2011. 

There was a relatively large decrease in percentage of supply held large addresses near the end of 2011 through early 2013, before large price increases. Additionally, there was a decrease in December 2018 that was likely caused by Coinbase redistributing its cold wallets.

Source: Coin Metrics Network Data Pro

Ethereum

Unlike BTC, Ethereum had a crowdsale to initially distribute Ether (ETH). The supply of ETH started off highly concentrated but has gradually become more distributed over time. 

The percentage of supply held by addresses with the largest balances (at least 1/1K of total supply) peaked at about 60% in July 2016. The amount held by these large addresses saw a significant decline as the ICO bubble deflated throughout the end of 2017 and into 2018. As of February 2020, these addresses hold about 40% of total ETH supply.

The percentage of supply held by relatively small addresses (with 1/100K of total supply and lower) has been steadily increasing since 2016. 

Source: Coin Metrics Network Data Pro

Litecoin

Litecoin (LTC) had several large dips in the amount held by large addresses (at least 1/1K of total supply) throughout 2013 just prior to the December 2013 price spike, and throughout 2017 before the January 2018 price peak. Interestingly, nearly 46% of supply is still held in large LTC account compared to 11% held in large Bitcoin accounts. 

Source: Coin Metrics Network Data Pro

Bitcoin Forks

Bitcoin forks inherit BTC’s supply distribution (at the time of forking), so may appear distributed simply because BTC itself is relatively distributed. But unlike BTC, Bitcoin Cash (BCH) supply held by large addresses has gotten more concentrated over time.

In August 2017, when it forked from BTC, about 14% of BCH supply was held by large addresses with balances of at least 1/1K of total supply. As of February 2020, large addresses hold about 29% of BCH, compared to about 11% for BTC.

Source: Coin Metrics Network Data Pro

Bitcoin SV (BSV) percentage of supply held by addresses with balance of at least 1/1K has remained relatively flat, outside of a significant dip in February 2019, and a sudden increase in June 2019. In August 2018, when BSV forked from BTC, these large addresses held about 26% of BSV supply. As of February 2020, they hold about 24%.

Source: Coin Metrics Network Data Pro

Ripple and Stellar

Ripple (XRP) and Stellar (XLM) are both account-based chains, and both have official foundations that hold a large percentage of supply. About 85% of total XRP supply is held by addresses with balance of at least 1/1K. 

About  95% of total XLM supply is held by addresses with a balance of at least 1/1K of total supply. This is largely because the Stellar Development Foundation (SDF) holds over half of XLM supply. According to the SDF’s mandate, it currently holds 29.4B XLM. Additionally, the SDF recently burned 50% of total XLM, bringing the supply down to 50B. These burned XLM still appear on-chain since they were sent to a burn address, and therefore get counted as part of the supply distribution. 

Source: Coin Metrics Network Data Pro

Tether

Tether, which is the largest stablecoin by most measures, has released tokens on multiple blockchains. For this analysis, we looked at the Omni (USDT-Omni), Ethereum (USDT-ETH), and Tron (USDT-TRX) versions of Tether separately.

All three versions of Tether started out 100% concentrated. But USDT-Omni and USDT-ETH have gotten increasingly distributed over time. This could be a signal that they are being used as a medium of exchange, which would explain why supply is flowing from addresses holding large balances to addresses holding smaller balances. The Tron version of Tether (USDT-TRX), however, has stayed almost 100% concentrated, which signals that it is likely not getting much usage as a medium of exchange (however, Tether was only introduced on Tron in May of 2019, so is still relatively new).

Also of note, the USDT-Omni distribution trend reversed and started becoming more concentrated in January 2018, near the peak of the market wide price bubble.

Source: Coin Metrics Network Data Pro

Conclusion

Cryptoasset supply distribution gives a clearer window into wealth distribution than any prior asset class, and also provides some interesting insights into trading patterns. The increasing distribution of assets like BTC and Tether is a positive sign that these assets may be getting real usage, and are ending up in the hands of more individual users. We will continue to analyze supply distribution and report on this in the future.

Network Data Insights

Summary Metrics

It was another positive week for the major cryptoassets. ETH continues its strong run, leading the pack in most metrics. Notably, ETH’s realized cap, which can be thought of as the average cost basis of all holders of the asset, increased by 3.6%, while BTC’s increased by 1.3%.

IOTA has been in the news recently after the network was shut down following a hack. We analyze the price implications of this incident in this week’s Market Data Insights section.

Network Highlights

The median transaction fee for both BTC and ETH has increased at least 60% over the last 30 days, outpacing all other major cryptoassets. Median block fees typically rise due to an increased demand for block space, potentially because of increased usage.

Source: Coin Metrics Network Data Pro

Dai (DAI), Paxos (PAX), USD Coin (USDC), and True USD (TUSD)  transfer counts have all been growing faster than Omni-based Tether (USDT), Ethereum-based Tether (USDT_ETH), and Tron-based Tether (USDT_TRX) over the last 30 days. Although Tether is still by far the largest stablecoin in terms of market cap, this may be an early sign that other stablecoins could start closing the gap in 2020.

Source: Coin Metrics Network Data Pro

Market Data Insights

Many assets were relatively flat for the week with a few important exceptions: ETH (+14%) and Tezos (XTZ) (+21%). 

The BTC options market has been pricing in increased volatility over the next several months as reflected in the spread between realized and implied volatility, in part because of elevated open interest in BTC futures markets. But it has yet to materialize. In fact, BTC has traded in a narrow range over the past week compared to other assets. The spread between BTC’s realized volatility and other assets has widened, most significantly in ETH. 

Source: Coin Metrics Reference Rates

Investigating Recent IOTA Price Action

Market efficiency and maturation is a recurring theme for The State of the Network. The recent IOTA incident is another valuable data point to benchmark the industry’s progress. 

At 12:00 PM (17:00 UTC) on Tuesday, February 12, 2020, the IOTA Foundation sent a tweet stating that they were investigating suspicious behavior with the Trinity wallet.

Less than 30 minutes later, IOTA announced on their Status Page that they were shutting down the Coordinator, effectively shutting down the network.

However, it was another 24 hours before IOTA sent a second tweet about pausing the Coordinator, saying they were working with law enforcement and cybersecurity experts to investigate a coordinated attack” and paused the Coordinator in order to protect users.

As the below chart indicates, the price was not particularly responsive to this news. In fact, the price did not even drop to levels seen on February 10th. The only noticeable change in price occurred around 08:00UTC on February 13th, roughly 15 hours after the first tweet and 8 hours before the second tweet. 

This lack of substantial price action is somewhat surprising given that the net effect was the shut down of IOTA.

Source: Coin Metrics Reference Rates

To our knowledge, none of the constituent exchanges for the CM Reference Rates halted trading in IOTA. This is notable for two reasons: 

  1. There was no way for users to deposit or withdraw IOTA once the Coordinator had been shut down. This means that only IOTA already on exchanges could be traded.
  2. More importantly, IOTA claims that the attacker was using exchanges to liquidate their stolen holdings, after some obfuscation, and that exchanges have flagged the applicable transactions.

One might expect these developments to contribute to reduced trade volume following an initial spike. As can be noted from the charts below, while there does appear to be a spike in trade volume, it primarily occurs only after the second IOTA tweet– the response to the first tweet was limited. Additionally, rather than dry up completely after the spike, trade volume appears to actually increase in some markets, even hours after the second tweet. 

A final interesting note regarding the trading activity: at various intervals, there appears to be large volume spikes across some markets prior to the first tweet from IOTA. The earliest social media activity we could find about the IOTA issue was on the IOTA Discord channel, starting at around 10:35AM EST on Wednesday, February 12th. This roughly co-incidents with the timing of a volume spike in the bitfinex-miota-btc-spot market, as can be seen in the chart below. 

Source: CM Market Data Feed

Note that Coin Metrics uses the ticker ‘miota’ to refer to IOTA.

CM Bletchley Indexes (CMBI) Insights

After a strong start to the week, most Indexes gave up their returns over the weekend to close the week out relatively flat. The CMBI Ethereum Index was the best performer of the week, reaching returns of 25% intra-week before finishing the week 14% up. The Bletchley 20 (mid-caps) had their first negative week for the year, finishing as this week’s worst performer, down 3%.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 5 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at [email protected]

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