Dissecting a Bitcoin Bull Market

By Lucas Nuzzi and the Coin Metrics Team

A pandemic, followed by global societal shutdowns, followed by rampant social unrest, followed by increased political polarization, followed by unprecedented levels of monetary interventionism.

This has been 2020.

And in the midst of all of this uncertainty and chaos, a Bitcoin bull market brewed. 

Two competing theories have transpired to explain BTC’s rapid rise to $19,000. Some have speculated that this rally is being predominantly driven by increased regulatory scrutiny in China, which has prevented miners and market participants from selling their BTC. Others attribute it to increased institutional participation after Bitcoin received a trove of endorsements from high-profile macro investors.

In this post, we will evaluate the merit of each of these narratives through the use of network data. 

Are Miners Driving This Rally? 

It is no secret that Beijing has been cracking down on Bitcoin businesses, from miners to exchanges. Earlier this month, news broke that both Huobi and OKex, two of the largest exchanges operating in China, were facing stronger regulatory scrutiny as part of the country’s new mandate to fight money laundering and fraud. Now, local industry observers have reported that the bank accounts of many Shenzhen miners have been frozen as part of this regulatory crackdown.

Media outlets have hypothesized that the recent run up in Bitcoin’s price was a direct result of this crackdown. If miners are unable to sell their BTC, a sustained disruption in the existing supply chain would ultimately generate scarcity. Thus far, however, solid evidence of the impact of the crackdown on mining operations has been anecdotal. Thankfully, we have devised metrics to assess this impact more objectively by tracking the movements of newly issued BTC.

Over the course of 2020, we have closely analyzed the on-chain custody behavior of both mining pool operators and their individual miners. We have found that unspent miner rewards provide a good proxy for aggregate mining pool custody. Since mining pools issue payouts to all of their participants, supply that sits 1 transaction from mining pools is a good representation of the holdings of individual miners. The culmination of this research was a new family of metrics released in October that can provide a view of when these network participants are accumulating, or disseminating, the bitcoins they mine.  

On an aggregate basis, the amount of Bitcoin held by mining pool operators has increased over the course of 2020. Notably, there was a sharp spike in April ahead of the halving and a steady increase followed. Conversely, Bitcoin held by individual miners has decreased in 2020, and at a particularly increased rate in November. 

If, in fact, there was a liquidity crunch predominantly driven by miners, one would expect the amount of BTC held by both pools (purple) and individual miners (green) to increase. Since individual miners are the liquidity gateways of newly issued bitcoins, any supply chain disruption would entail an increase in their holdings, whereas the opposite seems to be taking place.

Another metric that suggests miners have been able to sell their BTC as usual is the aggregate value of bitcoins sent by them. If miners were unable to sell their BTC, the aggregate outflows from their account would likely drop. However, that does not seem to be the case. As of November 21st, 809,217 BTC has left miner accounts. At this pace, the sum of bitcoins sent by miners in November will surpass the yearly average of 1,052,589 BTC sent per month.

Coupled with the aforementioned data on BTC held by miners, the lack of a clear change in miner outflows discredits the hypothesis that miners have not been able to sell as a result of a regulatory crackdown in China. 

Another troublesome factor in attributing the rally to miners is the size of BTC markets. At a market cap of over three hundred billion dollars, it is very unlikely that a rally of this magnitude could have been caused by miners alone. After all, miners are disincentivized to hoard BTC. They are rewarded in a volatile currency, whereas their operations entail monthly expenses paid in fiat. As such, their impact on the market decreases as less BTC is issued.

Nearly 100B USD was added to BTC’s total market capitalization over the course of November. It is hard to envision a scenario where miners alone were responsible for it given that they have received just shy of 360M USD thus far in November. As such, any impact of the regulatory crackdown on liquidity would likely be limited to that, which is too small to an impact of this magnitude.

The Role of Centralized Exchanges

Now, let us look at the on-chain footprint of centralized exchanges and assess their impact on the recent rally, not only in the context of increased regulatory pressure in the East, but also in light of other factors impacting exchanges in the West.

Historically, exchanges operating in China have been the primary target for regulators. It was no different this time. On November 2nd, Huobi’s Chief Operating Officer was reportedly arrested by Chinese authorities, although Huobi has denied the reports. In the days following the reports, Huobi experienced a mass withdrawal event as users grew worrisome. That resulted in a 60k BTC being withdrawn; a loss equivalent to 1B USD in deposits. 

Interestingly, Huobi is not the only exchange to experience a decrease in deposits. Over the course of 2020, the percentage of total BTC supply held by major exchanges has decreased on an aggregate basis, even if we remove Huobi from the equation. We have noticed an aggregate reduction of BTC holdings by the major exchanges we support (Bitfinex, BitMEX, Binance, Bitstamp, Bittrex, Gemini, Kraken, and Poloniex).

Even though Beijing’s crackdown on Bitcoin businesses has undoubtedly impacted Huobi, there might be other factors reducing assets-under-custody by exchanges in the West.

Stablecoins might have contributed to this decrease. For context, the total stablecoin market capitalization grew by a factor of 3 year-to-date, from 5.8B USD in January to a whopping 17.8B as of November. Since one of the biggest benefits of having deposits on centralized exchanges are fiat on/off-ramps, stablecoins might be competing for some of that utility. We have explored some of this in our report The Rise of Stablecoins, which provides an in-depth review of the drivers of stablecoin growth.

Another contributing factor might be the rise of “wrapped” versions of Bitcoin. While stablecoins might provide utility equivalent to an exchange’s fiat on/off-ramps, wrapped BTC might compete for other exchange services, such as lending.

Like stablecoins, Wrapped BTC (WBTC) and RenBTC (RENBTC) operate on the basis of user deposits of the underlying asset. Once the asset is deposited, a receipt is issued on an Ethereum smart contract, which then enables the asset to be used in Decentralized Finance (DeFi) applications, such as decentralized exchanges and lending pools.

The trade-offs between using centralized exchanges vs. wrapped assets are similar. In both scenarios, the depositor no longer has custody of the underlying asset. Although decentralized exchanges on Ethereum are far less efficient than centralized order book exchanges, the former offers access to a plethora of newly-issued assets. Additionally, holders of wrapped BTC can use it as collateral for loans and receive “yield” on their holdings. As such, the added utility of wrapped assets has likely contributed to the decrease in BTC held by major exchanges.

2017 Looks Different 

Although stablecoin issuance and WBTC have likely impacted overall AuC by centralized exchanges, these are still emerging trends. In order to understand why exchange AuC did not follow the rapid increase in prices, let us go back to the 2017 bull market.

On a relative basis, the 2017 bull market had an entirely different on-chain footprint than what we are witnessing today. Back then, BTC held by exchanges nearly doubled as BTC flirted with $20,000 USD for the first time.

Intuitively, it makes sense that a retail driven rally would increase BTC held by major exchanges. Since there are clear educational frictions in self-custodying assets, many retail investors prefer to defer custody to centralized service providers. Even though the industry has come a long way, especially in terms of hardware options for self-custody, there is still a steep learning curve that makes newcomers gravitate towards centralized exchanges.

So why isn’t BTC held by major exchanges increasing?

If the rally we are witnessing was retail-driven, the 100B USD added to bitcoin’s market cap would have likely been predominantly held on centralized exchanges. While it is true that our estimates are not capturing emerging exchanges, such as Deribit and FTX, Coinbase (given that they do not re-use addresses), or new on-ramps such as Paypal, one would still expect to see an increase in AuC on these established markets. However, the opposite seems to be taking place.


This suggests that there are other forces at play. On Nov. 21st, news outlets reported that Coinbase’s institutional AuC grew from 6B in April to 20B by 4Q20. If this rally is being driven by an influx of institutional investors, that would explain the downward trend in AuC by exchanges. Since institutional investors tend to operate predominantly in OTC markets, they bypass retail exchanges. 

Conclusion

In conclusion, our analysis of miner behavior coupled with custody data on Huobi shows no evidence to suggest this rally is being predominantly driven by a regulatory crackdown in China. The downward trend in AuC by retail exchanges may be an indication that this rally is being driven by increased institutional adoption. Given the use of OTC on-ramps, an increase in institutional participation would result in positive price action, but limited on-chain footprint, which is what we might be witnessing in this bull market.

Coin Metrics’ State of the Network: Issue 77 – The State of DeFi Tokens

Weekly Feature

The State of DeFi Tokens

By Nate Maddrey and the Coin Metrics Team

The following is an excerpt from a full-length report which has been truncated due to space limitations. Read the full report here.

Decentralized finance (DeFi) took over the crypto world during the summer. But it cooled off after September, and has taken a back seat to BTC and ETH since.

In this week’s Feature, we explore the rapid rise of DeFi tokens and the current state of DeFi’s market cap and usage. You can check out our DeFi data and recreate many of the charts featured in this piece using our free community charting tool

DeFi’s Third Act

Although it may seem like it popped up overnight, DeFi has been around for years. During 2018 early projects like MakerDAO (MKR) and 0x (ZRX) pushed the total DeFi market cap to over $5B, as Ether (ETH) price reached all-time highs. But the initial DeFi surge was dwarfed by this summer’s run, which saw the rapid entry of many new projects.

Source: Coin Metrics Network Data Charts

DeFi’s recent rise began in earnest in June with the launch of Compound protocol’s COMP governance token. COMP’s launch kickstarted the rise of decentralized lending and borrowing, which served as the initial fuel for DeFi’s surge. Compound lets users borrow cryptoassets like ETH, DAI, and USDC using crypto as collateral. It also lets users lend their cryptoassets and earn yield, which has become a cornerstone of DeFi investing. In addition to Compound, Aave protocol has grown to be one of the largest DeFi decentralized lending platforms. Aave originally launched the LEND token, which they recently transitioned to the AAVE token. 

Following COMP many other DeFi applications launched governance tokens during the summer of 2020. Yearn.finance, an application that automatically invests user’s funds into the highest yielding decentralized lending markets, launched the YFI governance token in mid-July. YFI was launched through incentivized liquidity pools which has become a popular way of launching DeFi tokens. YFI reached a market cap of over $1B by the end of August.

DeFi market cap peaked on September 18th shortly after the launch of Uniswap’s UNI governance token. Uniswap, the largest Ethereum-based decentralized exchange, has been the engine behind DeFi mania. Uniswap allows anyone to create a new token pair and immediately begin trading using decentralized liquidity pools, which helped new DeFi tokens launch and scale quickly. Uniswap trading volume increased from about $1M a day in early June to close to $1B a day in the beginning of September.

UNI was launched as an airdrop that rewarded previous Uniswap users and liquidity providers. Because of its sudden launch, UNI almost immediately catapulted DeFi market cap to a new all-time high. But soon after, the bubble began to burst. New UNI recipients started to sell their tokens en masse, causing UNI’s price to drop from a high of close to $7 to a low of less than $2. Additionally, a series of exploits and hacks led to large losses, which took more air out of the sector. 

Source: Coin Metrics Network Data Charts

But DeFi market cap has started to turn back around. After reaching a local low on November 4th, DeFi market cap has returned back to late September levels following a surge from BTC and ETH. If BTC and ETH continue to rise, DeFi could be a big benefactor. 

Usage Rebound

Similar to market cap, DeFi usage as measured by daily active addresses also peaked in September. Following the initial airdrop there were over 176K UNI active addresses on September 17th, by far the largest amount in DeFi history. But since then UNI daily active addresses have rapidly declined and leveled off at about 5K per day. 

Source: Coin Metrics Network Data Charts

Removing UNI from the above chart shows that other DeFi tokens are regaining usage. Excluding UNI, the overall number of active addresses still peaked in early September, mostly due to the rise and fall of SushiSwap (SUSHI). 

Source: Coin Metrics Network Data Charts

Continue reading “The State of DeFi Tokens” here

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) and Ethereum (ETH) continued their hot streaks this week. BTC averaged over 1M daily active addresses and continues to close in on the all-time high of 1.29M set in December 2017. BTC’s realized cap topped $128B on November 12th, the highest it’s ever been. ETH’s realized cap grew 3.9% week-over-week and is now over $36B, its highest level since September 2018. 

Network Highlights

After originally forking from Bitcoin in August 2017, Bitcoin Cash (BCH) is undergoing its own split. On Nov 15th, Bitcoin Cash forked into two chains: BCHA, and BCHN. At time of writing, BCHN appears to be winning, as little to no hash power is being devoted to BCHA.

Initially proposed as a “medium-of-exchange” alternative to BTC that could be used as a transactional currency, BCH has averaged less than $150M per day of adjusted transfer value for most of 2020. Comparatively, BTC is currently averaging over $4B of daily adjusted transfer value.

Source: Coin Metrics Network Data Charts

Although low transaction fees were often touted as one of the advantages of BCH, low fees likely hurt the long-term viability of the network. Transaction fees are paid to miners as an incentive for securing the network (in addition to block rewards). While low average fees are good for individual users, low total fees typically means that there’s low demand for block space, and ultimately low demand for using the network. BCH has had a total of less than $1.5M worth of transaction fees over its entire history. BTC had over $1.6M daily transaction fees last Friday.

Source: Coin Metrics Formula Builder

Similarly, BCH usage remains far behind BTC. The following chart shows the percent share of total active addresses across both BTC and BCH. BCH only has about 6% of active addresses, compared to 94% for BTC.

Source: Coin Metrics Network Data Charts

Market Data Insights

The decentralized exchange (DEX) tokens, UNI and SUSHI, made tremendous gains this past week as traders/speculators looked to place bets leading up to this Tuesday. November 17th marks the day that the initial UNI liquidity mining bonus program is originally scheduled to end.

For those unfamiliar, this program pays out Uniswap’s governance token, UNI, at a rate of 83,333 per day to liquidity providers in the pairs ETH/USDT, ETH/USDC, ETH/DAI, and ETH/WBTC. There are two base case outlooks on the end of this program: 

1) UNI will go up in value with decreased supply. 

2) UNI will decrease in value because liquidity will leave Uniswap due to lowered incentives, decreasing the value of the platform.

This creates an opportunity for the similar, alternative dex SushisSwap to attempt to attract that liquidity searching for a higher yield. And as of Monday afternoon they are changing their bonus structure to do just that, boosting the incentives paid out to those pools with programs ending on Uniswap.

governance proposal has been made for Uniswap to extend the program an additional two months while reducing the rewards by half. If voted in this proposal would not take effect until December 4, 2020, giving liquidity providers a fairly large window of time to move from the platform. The real winners from the continuation of the bonuses by both Uniswap and SushiSwap are the yield farming tokens which can continue to leverage these platforms to boost APY. 

UNI is up ~17% and SUSHI ~90% since Uniswap’s ‘community’ call last Friday

CM Bletchley Indexes (CMBI) Insights

A mixed week for CMBI and Bletchley Indexes that saw a cool down in most of the large cap market after several weeks of outperformance and a slight resurgence in mid and small caps. The exception to this was the CMBI Bitcoin, which had another strong week closing up 3% at $15,860.81. During this week, Bitcoin also experienced multi year highs, reaching levels that had not been experienced since January 2018.

The CMBI Ethereum finished the week down like many of the top 10 assets, closing at $444.11. The contrast in performance between Bitcoin and the other top 10 crypto assets can be observed in the returns of the CMBI10 and the CMBI10 Excluding Bitcoin, the former which closed the week up 1.8%, the latter down 1.6%.

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • We’re excited to announce the new Coin Metrics mobile app. View real-time cryptoasset pricing and relevant on-chain data in a single app!  Download for free here: https://coinmetrics.io/mobile-app/

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 ‌updates‌ ‌its‌ ‌mobile‌ ‌app‌ ‌

Your favorite crypto data mobile app now offers even more assets — DeFI assets!   Also, we’ve added Free Float Market Cap to our Total Market Cap and Realized Market Cap asset sorts.  And in case you missed our last update, below is the rundown of our mobile app features:

Features:

  • View Cryptoasset Prices:  Monitor our institutional quality cryptoasset prices. 
  • Chart Cryptoasset On-Chain Data:  View our best-in-class network data, including Realized Market Cap, MVRV (market cap/realized cap), CM’s Free Float Supply, Active Address Count, 1 Year Active Supply, Transaction Count, Total Fees, etc. at a point-in-time and overtime via our charting functionality.
  • Follow Coin Metrics Bletchley Indexes:  See real-time levels and key statistics like performance, volatility and  Sharpe ratios for our ten CMBI indexes, including our multi-asset (CMBI10) and hashrate indexes.
  • Tag/View Favorites:  Only interested in a few cryptoassets, no problem.  Tag your favorites or filter your view to include only the cryptoassets you most care about.

Available on the App Store and Google Play. 

The State of DeFi Tokens

By Nate Maddrey and the Coin Metrics Team

Decentralized finance (DeFi) took over the crypto world during the summer. But it cooled off after September, and has taken a back seat to BTC and ETH since.

In this week’s Feature, we explore the rapid rise of DeFi tokens and the current state of DeFi’s market cap and usage. You can check out our DeFi data and recreate many of the charts featured in this piece using our free community charting tool

DeFi’s Third Act

Although it may seem like it popped up overnight, DeFi has been around for years. During 2018 early projects like MakerDAO (MKR) and 0x (ZRX) pushed the total DeFi market cap to over $5B, as Ether (ETH) price reached all-time highs. But the initial DeFi surge was dwarfed by this summer’s run, which saw the rapid entry of many new projects.

Source: Coin Metrics Network Data Charts

DeFi’s recent rise began in earnest in June with the launch of Compound protocol’s COMP governance token. COMP’s launch kickstarted the rise of decentralized lending and borrowing, which served as the initial fuel for DeFi’s surge. Compound lets users borrow cryptoassets like ETH, DAI, and USDC using crypto as collateral. It also lets users lend their cryptoassets and earn yield, which has become a cornerstone of DeFi investing. In addition to Compound, Aave protocol has grown to be one of the largest DeFi decentralized lending platforms. Aave originally launched the LEND token, which they recently transitioned to the AAVE token. 

Following COMP many other DeFi applications launched governance tokens during the summer of 2020. Yearn.finance, an application that automatically invests user’s funds into the highest yielding decentralized lending markets, launched the YFI governance token in mid-July. YFI was launched through incentivized liquidity pools which has become a popular way of launching DeFi tokens. YFI reached a market cap of over $1B by the end of August.

DeFi market cap peaked on September 18th shortly after the launch of Uniswap’s UNI governance token. Uniswap, the largest Ethereum-based decentralized exchange, has been the engine behind DeFi mania. Uniswap allows anyone to create a new token pair and immediately begin trading using decentralized liquidity pools, which helped new DeFi tokens launch and scale quickly. Uniswap trading volume increased from about $1M a day in early June to close to $1B a day in the beginning of September.

UNI was launched as an airdrop that rewarded previous Uniswap users and liquidity providers. Because of its sudden launch, UNI almost immediately catapulted DeFi market cap to a new all-time high. But soon after, the bubble began to burst. New UNI recipients started to sell their tokens en masse, causing UNI’s price to drop from a high of close to $7 to a low of less than $2. Additionally, a series of exploits and hacks led to large losses, which took more air out of the sector. 

Source: Coin Metrics Network Data Charts

But DeFi market cap has started to turn back around. After reaching a local low on November 4th, DeFi market cap has returned back to late September levels following a surge from BTC and ETH. If BTC and ETH continue to rise, DeFi could be a big benefactor. 

Usage Rebound

Similar to market cap, DeFi usage as measured by daily active addresses also peaked in September. Following the initial airdrop there were over 176K UNI active addresses on September 17th, by far the largest amount in DeFi history. But since then UNI daily active addresses have rapidly declined and leveled off at about 5K per day. 

Source: Coin Metrics Network Data Charts

Removing UNI from the above chart shows that other DeFi tokens are regaining usage. Excluding UNI, the overall number of active addresses still peaked in early September, mostly due to the rise and fall of SushiSwap (SUSHI). 

Source: Coin Metrics Network Data Charts

COMP usage has been growing since mid-October. COMP active addresses hit a new all-time high of 8,264 on November 11th.

Source: Coin Metrics Network Data Charts

MakerDAO and MKR activity has also been growing since October. MKR active addresses hit an all-time high of 2,281 on October 4th, and topped 2K again on November 10th. MakerDAO recently reached a new record of over $2.3B total value locked (TVL), passing the $2B mark in early November. And DAI, the decentralized stablecoin issued by MakerDAO, also hit a milestone in the last week, reaching a supply of 1B for the first time. 

Source: Coin Metrics Network Data Charts

After dipping for most of October, YFI active addresses have shown some signs of life. There were 2,996 YFI active addresses on November 7th, the fourth highest daily total since its launch. YFI active addresses also topped 2K on November 10th. 

Source: Coin Metrics Network Data Charts

Conclusion

After bottoming out in October, DeFi appears to be in the beginnings of a resurgence. Usage trends show that COMP and MKR activity has been growing. Overall, DeFi continues to grow and mutate, as experimentation continues. With new money flowing into BTC and ETH, new DeFi tokens and applications are likely soon to follow. If recent trends continue, another DeFi wave may soon be on the horizon. 

To keep up with the latest DeFi trends and explore the assets in this article, check out our new DeFi data using our free community charting tool. 

Coin Metrics enhances its Community Data Visualization offering

Coin Metrics released several enhancements to the Network Data Visualization offering that includes our Network Data Charting Tool, Formula Builder Charting Tool, and our Correlation Tool released in July. New features include:

  • Coin Metrics Bletchley Indexes: create charts using CM’s indexes, including CMBI 10 and CMBI Hash Rate indexes
  • More Assets: see network data metrics for several new DeFi assets
  • Share Saved Charts Regardless of Permissions: share saved charts that include Pro metrics with all users, regardless of their level of access
  • Improved Metric Selection UI:  easily find the metric you are looking for based on your asset selection

If you are interested in learning more about our tools, please contact us at [email protected]!


ABOUT COIN METRICS

Coin Metrics is a leading provider of transparent and actionable cryptoasset market and network data. Coin Metrics delivers mature data across multiple formats to various industry stakeholders, including financial enterprises, funds, media and research outlets, and data/application providers. Coin Metrics’ data empowers its clients and the public to better understand, value, use, and ultimately steward public crypto networks.

Coin Metrics’ State of the Network: Issue 76 – Bitcoin: An Unprecedented Experiment in Fair Distribution

Weekly Feature

Bitcoin: An Unprecedented Experiment in Fair Distribution

By Lucas Nuzzi and the Coin Metrics Team

The following is an excerpt from a full-length report which has been truncated due to space limitations. Read the full report here.

Much has been written about the fundamental differences between Bitcoin and other asset classes. In fact, juxtapositions of Bitcoin and established commodities such as gold continue to lure swarms of newcomers into this industry, institutional and retail-alike.

But are there factors that make Bitcoin fundamentally different than other cryptoassets?

As the first-ever successful implementation of a digital currency, it’s common to see Bitcoin serve as a punching bag for technologists. To many of them, Bitcoin is a first-generation technology and, as such, it is plagued by a lack of transactional throughput and feature richness. But make no mistake: Bitcoin’s uniqueness goes far beyond the scope of technology. It is an unprecedented experiment in wealth distribution. 

In bull markets, the proverbial comparisons of Bitcoin and the likes of dial-up internet, or email in the 1980s, are vast and plentiful. Too often, these are part of deliberate marketing strategies pushed by proponents of emerging cryptoassets that reportedly succeed where Bitcoin has failed. Tragically, newcomers confronted by a strictly technological comparison framework are ultimately pushed to the margins, especially as debates turn hyper-technical. 

While it is undeniable that technology plays a role in evaluating the merits of any cryptoasset, there’s certainly more to the story. What technologists and, by extension, most newcomers often overlook is the fact that cryptoassets function as digital economies. And just like real-world economies, the technology through which currency is accounted for (governments, banks, payment networks) is often far less important than how that currency was and is effectively distributed (monetary policy and wealth distribution).

On-chain data provides a new paradigm for this type of economic analysis, as it makes possible the identification of inequitable wealth distributions at the asset level. After all, blockchains at their core provide a full history of ownership structures, and that history often speaks volumes. Cronyism, amongst other unfair supply distribution models, inescapably result in incredibly centralized monetary bases. Through on-chain data, we can identify ownership structures antithetical to Bitcoin’s and quantify the degree of wealth centralization within their digital economies. 

To paint a full picture of the factors that drive fair supply distribution, we will begin this post by reviewing Bitcoin’s early history. Then, we will take a closer look at distribution through mining and the impact of industrialization. Lastly, we will showcase two novel supply dispersion metrics to evaluate the wealth distribution of dozens of assets relative to Bitcoin. 

The Genesis of Magical Internet Money

Bitcoin’s early history is an attestation to the novelty of a purely digital currency. Its earliest transactors were likely enticed by Satoshi’s post on the P2P foundation forum, where he first introduced the system. Back then, only the technically savvy were able or willing to continuously run a network node. Even fewer participants were able to properly custody their wallets, as that would require some understanding of PGP encryption as well as a ton of patience to deal with the inevitable bugs in Bitcoin’s first wallet (if you can even call it that). There wasn’t even an exchange rate for the earliest of adopters to begin to fathom valuing their Bitcoins. 

Coupled with the aforementioned technical complexity, the results of early experiments on Bitcoin were disastrous: there is an exorbitant amount of BTC that is believed to have been permanently lost during that period. Transactors, after all, treated Bitcoin as it was back then: a curious experiment of digital monopoly money

Perhaps no other time series better showcases the unserious nature of early Bitcoin than the chart below. It demonstrates how it took until nearly 2011 for Bitcoin transactors to start using decimals (green line) when sending BTC. Until then, all transactions used full units of BTC (purple line) as users experimented with sending full bitcoins to one another. 

This is evidence of the stark difference between Bitcoin and all cryptoassets that followed. Bitcoin set a precedent for the convertibility of a digital asset and fiat currencies, like the US dollar. As a result, early adopters of other cryptoassets assumed value from day one, as opposed to carelessly experimenting. Although it is obviously better for end users to have reliable custody and some idea of asset valuation from the get-go, that experimentation in Bitcoin ultimately led to an unmatched level of supply turnover.

A direct way to measure supply turnover is through supply velocity metrics. As covered in previous SOTN issues, velocity measures the amount of times an average unit of supply has been transferred. It is generally calculated by dividing supply transferred by the total monetary base. In order to provide a better representation of short-term turnover, the particular variation of velocity showcased below filters activity by supply that was active in the trailing 1yr (instead of using total supply). 

A key element of Bitcoin’s unmatched distribution are the clear periods of high supply turnover, showcased as cycles of increased velocity. Such cycles depict early adopters making way to new adopters who, when the time comes, make way to even newer adopters. In the past, Bitcoin’s ferocious price rallies have been a considerable driving force for supply turnover. 

Again, precedents are important. The lack of a successful precedent for Bitcoin made it so that Fear, Uncertainty and Doubt constantly tormented the minds of early adopters, and newer adopters provided a way out through the markets. 

Fair Distribution by Design

As mentioned in the introduction, a cryptoasset’s underlying technology is most definitely not the sole determinant of its intrinsic value. However, it is still an important factor to consider as it often plays an enormous role in the distribution of supply. Bitcoin solved a decades-long problem in distributed computing dubbed the “Byzantine’s General Problem”, which has to do with reaching consensus on the validity of a statement amongst untrusted parties. What is truly remarkable is that Satoshi’s solution not only addressed the issue of distributed consensus, but did so with an activity that intrinsically fosters monetary decentralization: mining.

By design, Bitcoin mining is an activity that pushes the forces of fair distribution. In order to be profitable, miners must operate on long time horizons as they have fixed operational costs. However, the BTC reward issued for this activity widely fluctuates as Bitcoin’s price carries high volatility. This nudges miners to carefully manage their treasuries and constantly sell their holdings for operational purposes   like paying for electricity, as well as strategic requirements like upgrading their hardware to remain competitive. This ultimately increases supply turnover.

Apart from the effective validation of Bitcoin transactions, this activity strengthens the network by increasing the cost to attack it. By its very nature, Bitcoin’s underlying monetary policy fosters competition as its inflation rate decreases over time with every halvening. Even though miners have consolidated and fully industrialized as time progressed, the sheer size of existing operations leaves less room for them to speculate, which pushes new supply to change hands. 

Crypto Assets and Wealth Inequality

Thus far, we have covered the fundamental factors that have affected Bitcoin’s supply distribution. Now it is time to assess the extent to which these factors differentiate Bitcoin from other assets. In economics, there is extensive literature on wealth inequality and supply dispersion metrics. Unfortunately, the cryptoasset industry has not converged on an equivalent set of metrics. We hope to change that, and have devised a new set of metrics to quantify wealth inequality across many cryptoassets.

Continue reading “Bitcoin: An Unprecedented Experiment in Fair Distribution” here

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

It was a big week for Bitcoin (BTC) with market cap surging past $260B for the first time since January 2018. In addition to price, network usage was also up across the board. BTC active addresses grew by 17.9% week-over-week and averaged over 1M a day, after averaging only about 861K a day the previous week. Hash rate rebounded and grew 10.1% week-over-week after a precipitous drop likely caused by changing weather conditions in China. Daily transaction fees also continued to climb, averaging about $3M a day. Overall, the surge in usage and fundamental metrics is a positive sign that BTC is in a good position to continue its price growth. 

Ethereum (ETH) also had a big week, with release of the Ethereum 2.0 deposit contract which allows users to start locking up ETH in anticipation of Ethereum’s upcoming transition to proof-of-stake. The deposit contract will serve as a one-way bridge – once the funds are committed to the contract they cannot be subsequently unlocked and used on the main (Ethereum 1.0) chain. Therefore the supply locked into the contract is effectively taken out of circulation, at least until the launch of Ethereum 2.0. Once 524,288 ETH is locked into the contract Ethereum will launch Phase 0 of Ethereum 2.0, which will be a multi-year process aimed at exponentially increasing Ethereum’s scalability.  At time of writing, the deposit contract already holds about 49,500 ETH.

Network Highlights

On November 3rd an old Bitcoin address that had been dormant since 2013 suddenly came to life and transferred 69,369 BTC to an initially unknown destination. The transfer of almost 70K BTC was one of the largest single-day movements of dormant supply in Bitcoin’s history. The below chart shows the daily amount of BTC supply that has been revived after remaining inactive for at least five years. Since the initial transaction, it’s been revealed that the address was tied to early darknet marketplace Silk Road, and that the BTC was seized by the United States Department of Justice. 

Source: Coin Metrics Network Data Charts

On November 4th the percent of BTC unspent transaction outputs (UTXOs) in profit topped 98% for the first time since December 2017. Every time a Bitcoin transaction occurs at least one UTXO is created. UTXOs represent coins that can be spent as inputs to future transactions. We consider a UTXO “in profit” if BTC’s price at the time of the UTXO creation was lower than BTC’s current price. Theoretically, this means that the UTXO’s owner can sell their BTC at a profit (assuming that their initial transaction represented a purchase price). A high percentage of UTXOs in profit potentially signals that there is relatively low sell pressure, since there’s low risk of capitulation. But conversely it could signal that some investors may soon start taking profits if the potential gains become too good to pass up. 

Source: Coin Metrics Network Data Charts

Decentralized finance (DeFi) is showing signs of life. After declining over the last few months, yearn.finance (YFI) transaction count hit a new all-time high of 11.3K on November 7th. With ETH pumping, DeFi could be in store for a resurgence, although it remains to be seen whether we will ever return to the days of peak DeFi mania. 

Source: Coin Metrics Network Data Charts

Market Data Insights

We have rapidly reached levels over the past month not seen since late 2018 and are closing in on all-time highs. Bitcoin moved ~$2,000 week-over-week with a close of $15,483. The high for the week reached over $16,000 on some exchanges. 

Source: Coin Metrics Reference Rates

But the macroeconomic backdrop shifted a bit over the weekend. With the recent results from a Pfizer vaccine for COVID-19 and the “blue wave” not coming to fruition, the magnitude of future fiscal stimulus via central bank policy appears to have decreased. On Monday the markets reacted by punishing inflation hedges when money moved from safe havens to risk-on assets, sending gold down 5% for its worst day since August. Bitcoin ended the day down roughly 1%.

Source: TradingView.com

CM Bletchley Indexes (CMBI) Insights

It was an incredible week for all CMBI and Bletchley Indexes with most indexes returning above 10%. The CMBI Ethereum was the strongest performer, gaining momentum after the announcement of the Ethereum 2.0 staking contracts and closing the week at $451.79, up 14.9%. The CMBI Bitcoin also performed strongly, adding to its impressive run of 5 consecutive positive weekly returns, up 11.3% to $15,400.29.

The small cap assets showed a strong reversal after several weeks of negative returns, increasing 11% for the week. The mid caps performed well against the USD, increasing 4.5%, but underperformed the rest of the market.

Source: Coin Metrics CMBI

The CMBI Bitcoin Hash Rate reversed its consecutive down weeks after a difficulty adjustment last week. The index closed the week up 13%, spending most of the week in the 115-130 exahashes per second range.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • We’re excited to announce the new Coin Metrics mobile app. View real-time cryptoasset pricing and relevant on-chain data in a single app!  Download for free here: https://coinmetrics.io/mobile-app/

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.

Bitcoin: An Unprecedented Experiment in Fair Distribution

By Lucas Nuzzi and the Coin Metrics Team

Much has been written about the fundamental differences between Bitcoin and other asset classes. In fact, juxtapositions of Bitcoin and established commodities such as gold continue to lure swarms of newcomers into this industry, institutional and retail-alike.

But are there factors that make Bitcoin fundamentally different than other cryptoassets?

As the first-ever successful implementation of a digital currency, it’s common to see Bitcoin serve as a punching bag for technologists. To many of them, Bitcoin is a first-generation technology and, as such, it is plagued by a lack of transactional throughput and feature richness. But make no mistake: Bitcoin’s uniqueness goes far beyond the scope of technology. It is an unprecedented experiment in wealth distribution. 

In bull markets, the proverbial comparisons of Bitcoin and the likes of dial-up internet, or email in the 1980s, are vast and plentiful. Too often, these are part of deliberate marketing strategies pushed by proponents of emerging cryptoassets that reportedly succeed where Bitcoin has failed. Tragically, newcomers confronted by a strictly technological comparison framework are ultimately pushed to the margins, especially as debates turn hyper-technical. 

While it is undeniable that technology plays a role in evaluating the merits of any cryptoasset, there’s certainly more to the story. What technologists and, by extension, most newcomers often overlook is the fact that cryptoassets function as digital economies. And just like real-world economies, the technology through which currency is accounted for (governments, banks, payment networks) is often far less important than how that currency was and is effectively distributed (monetary policy and wealth distribution).

On-chain data provides a new paradigm for this type of economic analysis, as it makes possible the identification of inequitable wealth distributions at the asset level. After all, blockchains at their core provide a full history of ownership structures, and that history often speaks volumes. Cronyism, amongst other unfair supply distribution models, inescapably result in incredibly centralized monetary bases. Through on-chain data, we can identify ownership structures antithetical to Bitcoin’s and quantify the degree of wealth centralization within their digital economies. 

To paint a full picture of the factors that drive fair supply distribution, we will begin this post by reviewing Bitcoin’s early history. Then, we will take a closer look at distribution through mining and the impact of industrialization. Lastly, we will showcase two novel supply dispersion metrics to evaluate the wealth distribution of dozens of assets relative to Bitcoin. 

The Genesis of Magical Internet Money

Bitcoin’s early history is an attestation to the novelty of a purely digital currency. Its earliest transactors were likely enticed by Satoshi’s post on the P2P foundation forum, where he first introduced the system. Back then, only the technically savvy were able or willing to continuously run a network node. Even fewer participants were able to properly custody their wallets, as that would require some understanding of PGP encryption as well as a ton of patience to deal with the inevitable bugs in Bitcoin’s first wallet (if you can even call it that). There wasn’t even an exchange rate for the earliest of adopters to begin to fathom valuing their Bitcoins. 

Coupled with the aforementioned technical complexity, the results of early experiments on Bitcoin were disastrous: there is an exorbitant amount of BTC that is believed to have been permanently lost during that period. Transactors, after all, treated Bitcoin as it was back then: a curious experiment of digital monopoly money

Perhaps no other time series better showcases the unserious nature of early Bitcoin than the chart below. It demonstrates how it took until nearly 2011 for Bitcoin transactors to start using decimals (green line) when sending BTC. Until then, all transactions used full units of BTC (purple line) as users experimented with sending full bitcoins to one another. 

This is evidence of the stark difference between Bitcoin and all cryptoassets that followed. Bitcoin set a precedent for the convertibility of a digital asset and fiat currencies, like the US dollar. As a result, early adopters of other cryptoassets assumed value from day one, as opposed to carelessly experimenting. Although it is obviously better for end users to have reliable custody and some idea of asset valuation from the get-go, that experimentation in Bitcoin ultimately led to an unmatched level of supply turnover.

A direct way to measure supply turnover is through supply velocity metrics. As covered in previous SOTN issues, velocity measures the amount of times an average unit of supply has been transferred. It is generally calculated by dividing supply transferred by the total monetary base. In order to provide a better representation of short-term turnover, the particular variation of velocity showcased below filters activity by supply that was active in the trailing 1yr (instead of using total supply). 

A key element of Bitcoin’s unmatched distribution are the clear periods of high supply turnover, showcased as cycles of increased velocity. Such cycles depict early adopters making way to new adopters who, when the time comes, make way to even newer adopters. In the past, Bitcoin’s ferocious price rallies have been a considerable driving force for supply turnover. 

Again, precedents are important. The lack of a successful precedent for Bitcoin made it so that Fear, Uncertainty and Doubt constantly tormented the minds of early adopters, and newer adopters provided a way out through the markets. 

Fair Distribution by Design

As mentioned in the introduction, a cryptoasset’s underlying technology is most definitely not the sole determinant of its intrinsic value. However, it is still an important factor to consider as it often plays an enormous role in the distribution of supply. Bitcoin solved a decades-long problem in distributed computing dubbed the “Byzantine’s General Problem”, which has to do with reaching consensus on the validity of a statement amongst untrusted parties. What is truly remarkable is that Satoshi’s solution not only addressed the issue of distributed consensus, but did so with an activity that intrinsically fosters monetary decentralization: mining.

By design, Bitcoin mining is an activity that pushes the forces of fair distribution. In order to be profitable, miners must operate on long time horizons as they have fixed operational costs. However, the BTC reward issued for this activity widely fluctuates as Bitcoin’s price carries high volatility. This nudges miners to carefully manage their treasuries and constantly sell their holdings for operational purposes   like paying for electricity, as well as strategic requirements like upgrading their hardware to remain competitive. This ultimately increases supply turnover.

Apart from the effective validation of Bitcoin transactions, this activity strengthens the network by increasing the cost to attack it. By its very nature, Bitcoin’s underlying monetary policy fosters competition as its inflation rate decreases over time with every halvening. Even though miners have consolidated and fully industrialized as time progressed, the sheer size of existing operations leaves less room for them to speculate, which pushes new supply to change hands. 

Crypto Assets and Wealth Inequality

Thus far, we have covered the fundamental factors that have affected Bitcoin’s supply distribution. Now it is time to assess the extent to which these factors differentiate Bitcoin from other assets. In economics, there is extensive literature on wealth inequality and supply dispersion metrics. Unfortunately, the cryptoasset industry has not converged on an equivalent set of metrics. We hope to change that, and have devised a new set of metrics to quantify wealth inequality across many cryptoassets.

The first one we will showcase is the Supply Equality Ratio (SER). It is analogous to the 20:20 Ratio; a traditional wealth inequality metric that compares the average income of the richest 20% of a society to the poorest 20%. Instead of income, the SER looks at supply held by different accounts within a network. It compares the poorest accounts (the sum held by all accounts with a balance less than 0.00001% of the supply) against the richest accounts (the sum held by all the top 1% addresses). 

A high SER signifies high distribution of supply. As hypothesized, Bitcoin has the highest SER out of the assets evaluated, followed by Ether and Litecoin. This is remarkable, since Bitcoin is also the primary cryptoasset being custodied by large financial institutions; a trend that increases SER’s denominator and puts overall downward pressure on the ratio. The sustained increase in Bitcoin’s SER shows that, in spite of large institutions entering the space, Bitcoin is still very much a grassroots movement. The number of smaller accounts holding less than 1.85 BTC has continuously increased and counterbalanced the growth of top 1% addresses.

While SER provides a novel look into supply distribution that is not possible with most traditional assets, an important caveat is that a single individual can own many cryptoasset addresses. As such, an individual might hold many addresses and supply distribution does not directly map to an individual’s holdings. 

Another way to assess Supply Dispersion is through the Network Distribution Factor (NDF). This ratio emcompases a broader economic group, perhaps equivalent to a combination of the middle and lower classes. It is calculated by assessing the aggregate supply in addresses holding more than 0.01% of a cryptoasset’s supply and dividing that figure by the total supply.

Once again, Bitcoin has the highest distribution factor as measured by the NDF, followed by Decred, Litecoin and Ether. 

We are just scratching the surface when it comes to supply dispersion metrics, but SER and NDF provide a glimpse of Bitcoin’s unique distribution. In the future, we hope to continue to explore this area with better filtering heuristics to improve how addresses are aggregated at the wallet level.

Conclusion

In conclusion, Bitcoin’s turbulent history as the first-ever successful implementation of a cryptoasset contributed to high levels of supply turnover through the 2010s. Its fair issuance mechanism further supported distribution since miners have an intrinsic need to redistribute new issuance. Combined, these factors have made Bitcoin the most equitable cryptoasset in existence, as exemplified by the SER and NDF ratios.

Reference Rates Release Notes

Coin Metrics is pleased to announce the version 2.5 release of our Hourly Reference Rates and version 0.6 release of our Real-Time Reference Rates. Updated methodology documents for both products can be found here and here.

Coin Metrics produces the CM Hourly Reference Rates and Real-Time Reference Rates, a collection of prices rates quoted in U.S. dollars, published once per hour and once per second, for a set of cryptocurrencies. 

The release notes for this release include euro-quoted reference rates for Bitcoin and Ethereum, additions and terminations to our coverage universe, reconstitutions of our whitelisted markets, some recalculations of certain assets, and a change in the Market Selection Framework section of the methodology.

Euro-Quoted Reference Rates 

In this release, we offer euro-quoted reference rates for Bitcoin and Ethereum. These two reference rates are generated using euro-quoted constituent markets from major exchanges. You can access these rates using the ReferenceRateEUR metric in our version 4.0 API. Reference rates quoted in U.S. Dollars are available using the ReferenceRateUSD metric and the original ReferenceRate metric is preserved for backward compatibility. 

Coverage Universe Additions

This release expands our coverage universe to include 63 additional assets and brings our total coverage universe to a total of 305 assets. The 63 additional assets are included below.

  • Akropolis (akro)
  • Ampleforth (ampl)
  • Arweave (ar)
  • Balancer (bal)
  • bZx Protocol (bzrx)
  • Celo (celo)
  • Compound (comp)
  • Curve DAO Token (crv)
  • Caspian (csp)
  • DMM: Governance (dmg)
  • Polkadot (dot)
  • FOAM (foam)
  • Kin (kin)
  • Orchid (oxt)
  • THORChain (rune)
  • Solana (sol)
  • Serum (srm)
  • VeThor Token (vtho)
  • Wrapped Bitcoin (wbtc)
  • Wrapped NXM (wnxm)
  • Haven Protocol (xhv)
  • XYO (xyo)
  • YAMv2 (yamv2)
  • yearn.finance (yfi)
  • DFI.Money (yfii)
  • UMA (uma)
  • Energy Web Token (ewt)
  • Revain (rev)
  • Reserve Rights (rsr)
  • Avalanche (avax)
  • The Midas Touch Gold (tmtg)
  • JUST (jst)
  • Helium (hnt)
  • OriginTrail (trac)
  • Velas (vlx)
  • MXC (mxc)
  • Fetch.ai (fet)
  • Aurora (aoa)
  • IRISnet (iris)
  • Kleros (pnk)
  • Melon (mln)
  • ShareToken (shr)
  • Uquid Coin (uqc)
  • Harmony (one_harmony)
  • Tellor (trb)
  • Origin Protocol (ogn)
  • Travala.com (ava)
  • Loki (loki)
  • Hxro (hxro)
  • Wirex Token (wxt)
  • Cryptopay (cpay)
  • Filecoin (fil)
  • Uniswap (uni)
  • Swerve (swrv)
  • SushiSwap (sushi)
  • Aave (aave)
  • Elrond (egld)
  • Handshake (hns)
  • DIA (dia)
  • BOSAGORA (boa)
  • Ultra (uos)
  • Creditcoin (ctc)
  • renBTC (renbtc)

Coverage Universe Terminations

The following 6 assets are terminated from the coverage universe because they have been delisted from most major exchanges in our coverage universe. 

  • Aeron (arn)
  • PumaPay (pma)
  • Elrond (erd)
  • Matrix AI Network (man)
  • Everipedia (iq)
  • Aave (lend)

Reconstitution of Whitelisted Markets 

The whitelisted markets that serve as the input data source for the calculation of the reference rates for each asset was refreshed on 2020-09-28 as part of a regularly scheduled quarterly review. During each quarterly review, our Market Selection Framework is applied and the highest scoring markets are selected for each asset. 

Recalculations Due to Improvements in Historical Whitelisted Markets

Investigations of price anomalies resulted in minor modifications of historical whitelisted markets for a small number of assets. The following 25 reference rates received changes and historical values received minor changes. 

  • bcn-usd: recalculation from 2020-07-01 to 2020-09-28
  • cvt-usd: recalculation from 2019-12-11 to 2020-09-28
  • dent-usd: recalculation from 2020-01-23 to 2020-09-28
  • dta-usd: recalculation from 2020-01-23 to 2020-09-28
  • dx-usd: recalculation from 2020-04-09 to 2020-09-28
  • grin-usd: recalculation from 2019-05-23 to 2020-09-28
  • ignis-usd: recalculation from 2019-03-22 to 2020-09-28
  • leo-usd: recalculation from 2020-07-01 to 2020-09-28
  • mof-usd: recalculation from 2020-02-26 to 2020-09-28
  • nmr-usd: recalculation from 2019-01-28 to 2020-09-28
  • npxs-usd: recalculation from 2018-06-22 to 2020-09-28
  • paxg-usd: recalculation from 2020-04-08 to 2020-09-28
  • rif-usd: recalculation from 2019-01-16 to 2020-09-28
  • vsys-usd: recalculation from 2019-04-02 to 2020-09-28
  • zb-usd: recalculation from 2019-05-29 to 2020-09-28
  • dent-usd: recalculation from 2018-07-13 to 2020-09-28
  • npxs-usd: recalculation from 2018-06-22 to 2020-10-03
  • pnt-usd: recalculation from 2020-09-28 to 2020-10-03
  • fun-usd: recalculation from 2020-09-28 to 2020-10-28
  • pnk-usd: recalculation from 2020-08-26 to 2020-10-28
  • snx-usd: recalculation from 2020-09-28 to 2020-10-28
  • ignis-usd: outlier removed on 2019-10-02
  • snx-usd: all rates prior to 2020-04-09 were removed 
  • ubt-usd: all rates prior to 2020-03-11 were removed

Changes to the Methodology 

The Market Selection Framework section of the methodology was amended to exclude any constituent markets where volume, measured in U.S. dollars over the past 90 days, is less than 1 percent of the volume of the constituent market with the greatest volume. This change was implemented such that extremely low volume markets are less likely to be selected as a constituent market if higher volume markets of similar quality are available. Our research has indicated that this change will increase the quality of our reference rates. 

About the CM Reference Rates 

The CM Reference Rates are designed to serve as a transparent and independent pricing source that promote the functioning of efficient markets, reduce information asymmetries among market participants, facilitate trading in standardized contracts, and accelerate the adoption of cryptocurrencies as an asset class with the highest standards. The reference rates are calculated using a robust and resilient methodology that is resistant to manipulation and adheres to international best practices for financial benchmarks, including the International Organization of Securities Commissions’ (IOSCO) Principles for Financial Benchmarks. The Coin Metrics Oversight Committee and an independent governance structure protect the integrity of the reference rates and ensure the reference rates serve as sources of transparent and independent pricing.

Please reach out to Coin Metrics at [email protected] for more information on the CM Reference Rates.

Coin Metrics’ State of the Network: Issue 75 – Following Flows: A Look at Miners’ On-Chain Payments

Weekly Feature

Following Flows: A Look at Miners’ On-Chain Payments

By Karim Helmy and the Coin Metrics Team

The following is an excerpt from a full-length report which has been truncated due to space limitations. Read the full report here.

Key Takeaways

  • Using a new methodology that looks at addresses one hop out from the coinbase transaction, this report quantifies miner holdings and activity. This approach improves on previous attempts at tracking miner spending, which inadvertently measured pool operator activity rather than miner behavior.
  • Miners accumulated an additional 318,000 BTC in the year leading up to the halving, from trough to peak.
  • With supply held by miners gradually decreasing and net flows from their addresses stabilizing, miners appear to be exerting less influence on the network.
  • Miner flow and supply metrics will be made available in the upcoming version 4.8 release of Network Data Pro.

Miners and Markets

In addition to their role in securing the network, miners have a profound effect on Bitcoin’s market dynamics. Because they can receive newly issued bitcoin rather than buying it, miners are natural net sellers of the asset. This effect is further compounded by the fact that miners’ operating expenses, chiefly electricity and rent, are primarily fiat-denominated, while their revenue is earned in bitcoin.

Using previously-unavailable data on accounts that have interacted with these addresses, this feature examines miners’ activity, assessing the drivers and impacts of their spending.

While on-chain data indicates miners’ influence on the network is gradually decreasing, they remain key players in the ecosystem with access to large amounts of capital. To help our users understand these actors, Coin Metrics is making a broad slice of miner-related data available in the upcoming version 4.8 release of Network Data Pro. Using this data, this feature finds that the supply held by miners has generally decreased over time and that the flows of funds to and from miners and pools have been dampened by the network’s successive halvings.

Summarizing Supply

To calculate miner flows, we begin by aggregating all addresses that have received payment from a coinbase transaction and labeling those as 0-hop addresses. All the addresses in this set, along with those that have received payment from an address in this set, are then tagged as 1-hop addresses.

Because of how mining pool wallets are typically structured, with pools initially receiving the block reward and only later distributing it to miners, 0-hop addresses generally represent mining pools and 1-hop addresses generally represent miners. For this reason, existing systems that attempt to extrapolate miner behavior from the spending habits of 0-hop addresses are theoretically unsound and do not measure what they purport to. Instead, they measure pool operators’ activity.

Admittedly, tagging miners and pools based on distance from a coinbase transaction is an imperfect technique. This is especially true when the methodology is applied to the early network, in which solo mining and alternative pool models were more popular. Because the first mining pool, Slush Pool, mined its first block in December of 2010, measurements from before this date in particular should only be used for reference. Furthermore, miner addresses that have not received funds from a 0-hop address will not be tagged. All told, though, this heuristic represents a significant improvement over the current state of the art and should accurately capture broad trends.

Miners, especially those active in the network’s early days, control a significant amount of bitcoin. The number of coins held by both 0-hop and 1-hop addresses has generally declined throughout the network’s history. H2 2019 and H1 2020 saw a significant reversal in this trend in the run up to the halving, however, with miners accumulating an additional 383,000 BTC from trough to peak. This effect was primarily confined to 1-hop addresses, with 0-hop supply remaining roughly flat—the bulk of this accumulation would therefore have remained undetected by previous estimation techniques. 

Several jumps in the supply held by miners are visible. These spikes are typically caused by addresses with significant balances mining their first block or making their first interaction with a previously-tagged 0-hop address. The most prominent of these jumps occurred on August 16, 2012, when a whale holding over half a million BTC received part of the coinbase reward for block 194,256. New entrants were also responsible for the increase in miner-controlled supply before this year’s halving.

Due to inflation, the gradual reduction in supply held by miners and pools is even more significant when viewed in the context of total supply. This decrease is in line with a general increase in bitcoin’s supply dispersion. It’s also consistent with more widespread adoption of the pool model, which implies that non-mining addresses are becoming less likely to be superfluously tagged as 1-hop addresses.

Even today, though, miners and pools control a substantial chunk of the total bitcoin supply.

Pools and Payments

The flow of funds to and from these groups is another potent on-chain signal. Because pools are typically the immediate recipients of coinbase rewards, 0-hop flows are a useful indicator of mining pool activity. With the exception of several spikes, the most notable of which is attributable to the aforementioned whale, 0-hop inflows and outflows have both trended downward in BTC terms since the early days of the network.

Continue reading “Following Flows: A Look at Miners’ On-Chain Payments” here

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Bitcoin (BTC) network metrics had a mixed week. BTC transaction fees broke out this past week, growing 123.3% week-over-week and averaging close to $3M per day. BTC had almost twice the amount of total fees as Ethereum (ETH) this past week, reversing the trend of the last four months.

But other BTC metrics dropped. Most notably, hash rate dropped by 18.2% week-over-week after it almost reached new all-time highs just a few weeks earlier. Block production slowed as a result of the hash rate drop, which led to a drop in the overall amount of transactions and transfers. For more about this and the reasons behind the sudden drop see today’s Network Highlights section.

One other thing to note: USDC had over $11B of transfer value (adjusted) on October 26th,  smashing its previous all-time high of $2.11B. However the huge spike was likely due to the recent Harvest Finance exploit, which involved a series of USDC flash loans. 

Network Highlights

On October 29th and 30th BTC median transaction fee reached over $7, its highest level since January 2018. While there are many factors at play, the median fee spike is an interesting example of how weather conditions in a specific region of the world can have a ripple effect across the entire Bitcoin network.   

Source: Coin Metrics Network Data Charts

From October 24th to 28th Bitcoin’s hash rate suddenly began to fall, dropping by about 35% in total. Hash rate often fluctuates but this was a particularly large drop, especially considering that price was simultaneously rising which typically attracts more miners to the network.

Although it’s difficult to pin down the exact cause of the drop, the leading theory is that it was related to the end of the rainy season in southwestern China. During the wet season there’s excess water which is used for hydro energy, resulting in relatively cheap electricity. But when the weather dries up many miners are forced to move their operations to different locations in search of cheaper electricity. 

The sudden drop in hash rate caused the average time between new Bitcoin blocks to shoot up its highest levels in years. Less hash rate devoted to finding new blocks means that less blocks are produced. The following chart shows hash rate (left hand axis) vs mean interval between blocks in seconds (right hand axis) smoothed using a 7-day rolling average.

Source: Coin Metrics Network Data Charts

While block production slowed, incoming transactions did not. However, there was suddenly less block space to process the incoming transactions, due to the decrease in hash rate. This led to a large surge in the amount of unconfirmed transactions in the Bitcoin mempool. Despite the mempool surge, the on-chain transaction count dropped, as a much larger proportion of those transactions were stuck pending in the mempool waiting for some open block space. 

Source: Coin Metrics Network Data Charts

All together, this led to the surge in BTC transaction fees. Paying a higher fee leads to a higher chance that miners will prioritize the transaction and include it in a block. With block space at a premium, users were willing to pay higher and higher fees to try to get their transactions confirmed in a timely manner.

If the hash rate drop was truly caused by migrating Chinese miners we should see hash rate bounce back up in the upcoming weeks as operations get back up and running. It will be interesting to monitor moving forward, especially as more and more miners move to frontier markets like Iran, which are less weather-dependent.

Market Data Insights

Bitcoin (BTC) was clearly the main narrative when we look back on the month of October. BTC boomed following the narratives of inflation fears, election hedges, and the parade of companies moving some portion of their balance sheet into the asset class. BTC ended the month up ~30%, which puts it just under one standard deviation of monthly returns from the mean of 31% over the past 5 years.

Source: Coin Metrics Market Data Feed

In terms of absolute U.S. dollar moves, October was a notable close. With a gain of $3,194 from Oct. 1 to 31, there has only been 1 month in the last 5 years with a larger move. That month was December 2017, where Bitcoin moved $3,432 from $10,711 to $14,149. This gives the recent move some valuable context. 

One of the reasons that this recent move feels ‘healthier’ is the relatively low levels of realized volatility. Even though the 30 day moving average recently moved back up following last week’s price action, it still remains below the 50 mark and continues to trade in a historically low range.

CM Bletchley Indexes (CMBI) Insights

Again this week was characterized by the strength in large cap assets, in particular Bitcoin. The CMBI Bitcoin was the strongest performer of the CMBI and Bletchley Indexes, closing the week at $13,832.05, up 6.1%. The CMBI Ethereum did not fare as well this week, closing down 3.6% at $393.23. 

Bitcoin’s strong performance resulted in losses across the rest of the asset class, evidenced by the negative performance of all of the multi-asset indexes that do not have Bitcoin as a constituent. 

Source: Coin Metrics CMBI

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • We’re excited to announce the new Coin Metrics mobile app. View real-time cryptoasset pricing and relevant on-chain data in a single app!  Download for free here: https://coinmetrics.io/mobile-app/

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.

Following Flows: A Look at Miners’ On-Chain Payments

By Karim Helmy and the Coin Metrics Team

Key Takeaways

  • Using a new methodology that looks at addresses one hop out from the coinbase transaction, this report quantifies miner holdings and activity. This approach improves on previous attempts at tracking miner spending, which inadvertently measured pool operator activity rather than miner behavior.
  • Miners accumulated an additional 318,000 BTC in the year leading up to the halving, from trough to peak.
  • With supply held by miners gradually decreasing and net flows from their addresses stabilizing, miners appear to be exerting less influence on the network.
  • Miner flow and supply metrics will be made available in the upcoming version 4.8 release of Network Data Pro.

Miners and Markets

In addition to their role in securing the network, miners have a profound effect on Bitcoin’s market dynamics. Because they can receive newly issued bitcoin rather than buying it, miners are natural net sellers of the asset. This effect is further compounded by the fact that miners’ operating expenses, chiefly electricity and rent, are primarily fiat-denominated, while their revenue is earned in bitcoin.

Using previously-unavailable data on accounts that have interacted with these addresses, this feature examines miners’ activity, assessing the drivers and impacts of their spending.

While on-chain data indicates miners’ influence on the network is gradually decreasing, they remain key players in the ecosystem with access to large amounts of capital. To help our users understand these actors, Coin Metrics is making a broad slice of miner-related data available in the upcoming version 4.8 release of Network Data Pro. Using this data, this feature finds that the supply held by miners has generally decreased over time and that the flows of funds to and from miners and pools have been dampened by the network’s successive halvings.

Summarizing Supply

To calculate miner flows, we begin by aggregating all addresses that have received payment from a coinbase transaction and labeling those as 0-hop addresses. All the addresses in this set, along with those that have received payment from an address in this set, are then tagged as 1-hop addresses.

Because of how mining pool wallets are typically structured, with pools initially receiving the block reward and only later distributing it to miners, 0-hop addresses generally represent mining pools and 1-hop addresses generally represent miners. For this reason, existing systems that attempt to extrapolate miner behavior from the spending habits of 0-hop addresses are theoretically unsound and do not measure what they purport to. Instead, they measure pool operators’ activity.

Admittedly, tagging miners and pools based on distance from a coinbase transaction is an imperfect technique. This is especially true when the methodology is applied to the early network, in which solo mining and alternative pool models were more popular. Because the first mining pool, Slush Pool, mined its first block in December of 2010, measurements from before this date in particular should only be used for reference. Furthermore, miner addresses that have not received funds from a 0-hop address will not be tagged. All told, though, this heuristic represents a significant improvement over the current state of the art and should accurately capture broad trends.

Miners, especially those active in the network’s early days, control a significant amount of bitcoin. The number of coins held by both 0-hop and 1-hop addresses has generally declined throughout the network’s history. H2 2019 and H1 2020 saw a significant reversal in this trend in the runup to the halving, however, with miners accumulating an additional 383,000 BTC from trough to peak. This effect was primarily confined to 1-hop addresses, with 0-hop supply remaining roughly flat—the bulk of this accumulation would therefore have remained undetected by previous estimation techniques. 

Several jumps in the supply held by miners are visible. These spikes are typically caused by addresses with significant balances mining their first block or making their first interaction with a previously-tagged 0-hop address. The most prominent of these jumps occurred on August 16, 2012, when a whale holding over half a million BTC received part of the coinbase reward for block 194,256. New entrants were also responsible for the increase in miner-controlled supply before this year’s halving.

Due to inflation, the gradual reduction in supply held by miners and pools is even more significant when viewed in the context of total supply. This decrease is in line with a general increase in bitcoin’s supply dispersion. It’s also consistent with more widespread adoption of the pool model, which implies that non-mining addresses are becoming less likely to be superfluously tagged as 1-hop addresses.

Even today, though, miners and pools control a substantial chunk of the total bitcoin supply.

Pools and Payments

The flow of funds to and from these groups is another potent on-chain signal. Because pools are typically the immediate recipients of coinbase rewards, 0-hop flows are a useful indicator of mining pool activity. With the exception of several spikes, the most notable of which is attributable to the aforementioned whale, 0-hop inflows and outflows have both trended downward in BTC terms since the early days of the network.

Miner revenue, or income from block rewards, accounts for the bulk of 0-hop inflows. While miner revenue varies in the short term due to fluctuations in fees and the number of blocks mined, it is relatively stable across epochs.

While inflows and outflows are strongly correlated, outflows are much more volatile because they lack this protocol-mandated support, and because miners can choose when they would like to withdraw funds from mining pools’ wallets. The effects of the 2016 and 2020 halvings are apparent in a reduction in both types of flows. Since the 2020 halving, the value of inflows has generally exceeded that of outflows, a reversal of the historical norm.

Miners’ Money

While 0-hop flows are useful for tracking pool operators’ payments, in today’s standard wallet architecture, they do not represent transfers performed by miners themselves. In most pools, block rewards are instead received by an address controlled by the pool operator, who custodies funds until miners are paid out on a regularly-scheduled interval or choose to withdraw.

Under the pooled mining model, flows from addresses one hop out from the coinbase transaction more closely approximate miner spending. This report is one of the first attempts at analyzing 1-hop flows. Due to the much larger number of relevant addresses, the lack of an underlying support, and the high velocity of money, these flows are much larger and significantly more volatile than their 0-hop counterparts.

For analyzing flows in the early days of the network, before pools became the most common way to mine, 0-hop flows may be a more appropriate tool. Even today, 1-hop flows are only an approximation of miner activity, since pools’ wallet structures vary and exchange addresses may be erroneously included in these flows. By and large, though, this model represents a more holistic view of miner spending under today’s network conditions.

Like 0-hop flows, 1-hop inflows and outflows are closely related. Since block rewards represent only a small fraction of 1-hop inflows, both inflows and outflows are very volatile and the effect of the halving on this category of flows is less apparent.

Over the last year or so, flows to and from miner addresses have trended slightly upward, indicating heightened levels of activity. Because net flows have remained roughly constant and are generally becoming less volatile, this heightened activity does not appear to be reflected in an increase in influence on the broader network.

The tight coupling between inflows and outflows shows that miners, on aggregate, tend to move coins that come into their possession out of their addresses immediately.  Given that derivatives marketplaces and fiat lenders typically require custody of coins, these flows do not rule out miners’ use of financial instruments to hedge their exposure to bitcoin’s price. However, survey data from Cambridge’s Third Global Cryptoasset Benchmarking Study suggests that adoption of these tools is low, with miners primarily relying on holding and selling bitcoin to meet their desired level of risk. The high amount of turnover then seems to indicate that miners are active market participants, habitually selling most newly-received coins.

Dollar Decisions

Because miners’ expenses, profits, and losses are dollar-denominated, viewing their flows through a dollar-value lens is useful. Since 0-hop flows are largely comprised of block rewards, the plot of their dollar values closely resemble that of miner revenue.

Because of their mutual dependence on the price of bitcoin, the plot of USD-denominated miner flows resembles that of pool flows on a larger scale. Unlike pool flows, though, miner flows have been trending upwards, even briefly surpassing their 2017 high in late 2019. This indicates broader miner activity across the network in dollar terms.

Compound Considerations

Viewed separately, inflows and outflows are useful for gauging the amount of economic activity that miners are engaging in. 

For most of the network’s history, net flows from 0-hop addresses have been slightly negative, with these addresses typically spending more than they receive. While net flows were volatile in the network’s early days, their volatility has gradually decreased over time, likely due to the network’s halvings.

The dampening in 0-hop net flow volatility has continued in recent years. In the past few months, there’s been a reversal in the net flows’ historical negativity, with inflows slightly exceeding outflows since the most recent halving.

Like, 1-hop net flows are much more volatile than their 0-hop counterparts. Like 0-hop net flows, 1-hop net flows have generally been negative. These flows have also experienced a gradual dampening in volatility, indicating a gradual reduction in miners’ effect on liquidity.

Another tool for analyzing flows is the Miner’s Rolling Inventory, or MRI, which is the ratio of miner outflows to miner revenue. 0-hop MRI is useful for measuring whether miners are keeping their funds in mining pool wallets, represented by a ratio below 100%, or withdrawing them, represented by a value above 100%.

Since 0-hop flows are closely tethered to miner revenue, MRI has remained close to 100% for most of the network’s history. Volatility in this metric has gradually lowered in line with the dampening in 0-hop outflow volatility.

Compared to 0-hop MRI, 1-hop MRI provides a more accurate view of the relationship between miners’ spending habits and revenue. With 1-hop flows remaining comparatively flat throughout the network’s history and successive halvings reducing issuance, 1-hop MRI has grown in spurts. Because 1-hop spending is at about an order of magnitude higher than miner revenue, 1-hop MRI has measured in the thousands of percentage points for much of the network’s history.

Where do we go from here?

On-chain metrics like miners’ holdings and net transfer volumes indicate that miners’ influence on the network is slowly waning. Nonetheless, they’re still responsible for a substantial amount of activity, and control a significant portion of the total bitcoin supply. Some metrics, like gross flow volumes, also hint at increasing miner activity in both dollar and bitcoin terms.

As the only direct recipients of issuance, miners and pools also exercise a less-easily quantifiable influence on the network, and the metrics outlined in this article only scratch the surface of miner behavior. In the future, we hope to analyze flows from miners to exchanges, measuring their market impact more directly. We also hope to assess the active supply held by miner addresses, which would help to filter out lost coins from the network’s early days, as well as take into account individual pools’ wallet structures, ultimately allowing for a more granular assessment of miner behavior. 

Thanks to Celia Wan for suggestions and edits.