Coin Metrics is now publishing our CM Reference Rates live on Pyth Network! Pyth Network is an on-chain oracle that publishes financial market data to multiple blockchains. Now decentralized applications or off-chain applications needing a reliable pricing source via an on-chain oracle can consume our CM Reference Rates or the Pyth aggregate price. Coin Metrics and Pyth Network previously posted more information about our involvement with Pyth when we joined as publisher here and here.
We publish the CM Reference Rates continuously, multiple times per second, to both the Solana mainnet and Pythnet. Applications residing on Solana can consume our prices via the Solana mainnet and applications residing on other EVM-compatible chains like Ethereum, BNB, Avalanche, and several others can consume our prices via Pythnet.
Coin Metrics is publishing our CM Reference Rates for a wide selection of cryptoassets and fiat currencies. For each asset, we also publish a confidence interval specific to the asset, reflecting the situation that the same asset can trade for a wide range of prices across multiple trading venues and the uncertainty in our estimates. The interpretation of the confidence interval is one standard error of our prediction of the true price. Applications can use our confidence interval to protect users and the protocol during times of market stress and compute a range in which the true price lies. Then, the protocol or application can take the most conservative action that preserves the solvency and stability of the protocol. For instance, if a protocol needs to continuously monitor a user’s collateral position, the protocol can value it at the lower bound of the price of the range and liquidate the user’s collateral position if needed using this lower bound.
About the CM Reference Rates and CM Prices
The CM Reference Rates are published once a day, once an hour, once a minute, once a second, and once every 200 milliseconds and utilize volume-weighted median, time-weighted average, and inverse price variance-weighted median techniques. Common use cases for the CM Reference Rates include research, backtesting, calculating net asset value for investment funds, calculating closing prices for indexes or financial benchmarks, serving as a data source for on-chain price oracles, risk management, indicative intraday values for investment funds and financial benchmarks, and settling financial derivatives. The CM Reference Rates in combination with our CM Principal Market Prices which we collectively refer to as the CM Prices.
The CM Prices are designed to serve as a set of transparent and independent pricing sources 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 CM Prices are calculated using robust and resilient methodologies that are resistant to manipulation and adhere to international best practices for financial benchmarks, including the International Organization of Securities Commissions’ (IOSCO) Principles for Financial Benchmarks. The Coin Metrics Oversight Committee (the “Oversight Committee”) and an independent governance structure protect the integrity of the CM Prices and ensure the CM Prices serve as a source of transparent and independent pricing.
Pyth is a first-party financial oracle network designed to publish continuous real-world data on-chain in a tamper-resistant, decentralized, and self-sustainable environment. The network incentivizes market participants — exchanges, market makers, and financial services providers — to share directly on-chain the price data collected as part of their existing operations. The network then aggregates this first-party price data on-chain and makes it available for free to either on- or off-chain applications. Pyth data end-users will have the option of paying data fees to hedge against potential oracle failure. This data fee model is part of Pyth’s incentive mechanism design which aims to attract more publishers to the network and, in turn, enhance network robustness. The Pyth Data Association was created in support of the Pyth network and is overseen by a board of directors elected by members of the Pyth network. For more information, visit https://pyth.network/