Off-Chain Cryptoasset Data: A Closer Look
Understanding cryptoasset off-chain data and its differences and similarities to traditional finance data.
The very nature of the blockchain technology on which cryptoassets are built means their data metrics and KPIs can be fundamentally different from traditional securities. For example, access to on-chain data produced by cryptoasset transactions is integral to understanding the health and activity of a cryptoasset’s blockchain network, helping a financial institution (FI) to make more informed investment decisions. There is also off-chain data that shows the activity of a blockchain network that happens outside the core blockchain on supplementary ‘layer 2’ infrastructure. This additional blockchain layer increases transaction execution speed because no validation is required from nodes operating on the core blockchain.
An example of this is Bitcoin’s Lightning Network, which can settle hundreds of thousands of transactions per second before sending these transactions to the main blockchain. Bitcoin’s core blockchain can only settle around seven transactions per second.
However, it is also important to note that understanding cryptoassets also requires market data - something which FIs are rather more accustomed to in the traditional finance world. To be clear, all market data is off-chain data but not all off-chain data is market data. As highlighted above, off-chain data includes data from additional blockchain layers outside of the core blockchain.
Generally, market data in the cryptoasset space can be split into the following categories:
Real-time and Historical Pricing Data of Cryptoassets from Centralised Exchanges: Current and historical spot pricing data from the largest centralised cryptoasset exchanges (such as Coinbase, Kraken and Binance). This includes coverage for Bitcoin and other cryptoassets called altcoins, a portmanteau of ‘alternative’ and ‘coin’, with respect to Bitcoin, which includes networks such as Ethereum, Ripple and Solana. This also includes coverage for stablecoins, which seek to provide price stability in the crypto market by having an algorithmic peg to a certain value. For example, Tether USDT is one of the largest stablecoins and is typically redeemable on a one-for-one basis against the US Dollar. Stablecoins are often used as a means of payment for centralised and decentralised cryptoasset transactions. Crypto exchanges have their own, unique market data APIs that FIs can leverage, typically through data vendors that provide similar services similar to those offered by companies like Bloomberg, Factset, and LSEG in traditional asset classes.
Other Crypto-native Data: Includes key details such as market capitalisation, tokenomics (including total supply and total number of coins in circulation of a particular cryptoasset network), total value locked, issue price, whitepaper and official website. A whitepaper is the founding documentation of a particular cryptoasset, which outlines key information about the network, such as its purpose, key stakeholders, tokenomics and other information.
Decentralised Exchange Data: Decentralised Exchanges (DEXs) are online cryptoasset exchanges that connect users directly on a blockchain so they can trade cryptoassets without an intermediary. DEXs establish the prices of various cryptoassets against each other algorithmically and use “liquidity pools” — in which investors lock funds in exchange for interest-like rewards — to conduct trades. When assessing DEX data, FIs should understand the main liquidity providers and crypto wallet activity. In DEX trading, participants connect their crypto wallets directly to an exchange via the wallet interface without needing to send assets to an exchange.
Cryptoasset Derivative Market Data: Including futures, options and swaps data as seen in traditional markets. In particular, futures and options provide significant volumes. Due to the leverage offered by crypto exchanges, several of them have dynamic liquidation policies to help manage risk. These liquidations in derivatives markets can propagate across exchanges and into the spot market and affect price volatility.
Full Order Book Data: Full order book data for centralised exchanges including an aggregate order book across all main exchanges. This order book data is used to match buyers and sellers and is not etched into the core blockchain. The centralised exchange hosting the order book has full control of the market data and it decides how much of this data is made publicly available. This is one reason as to why it is crucial for FIs to also have access to on-chain data as it can plug information gaps that may be prevalent on a particular exchange and therefore help FIs to make more informed trading decisions.
VWAP, TWAP, OHLCV: Cryptoasset data can include a range of price-based algorithmic indicators that provide insight into the price changes of a cryptoasset over time. These include volume-weighted and time-weighted average price, along with open, high, low, close and volume data.
Cryptoasset data represents a new paradigm for financial data, with the intricacies of blockchain network activity needing to be understood for FIs to increase exposure to this burgeoning asset class. At the same time, the similarities of cryptoasset data to traditional finance data should give some FIs the confidence to increase cryptoasset exposure, with confusion and uncertainty around its integration with traditional finance systems still acting as a roadblock to greater adoption.
More to follow.