Coin Metrics Adds Five Exchanges to it’s ‘Trusted Spot Volume’ List

Coin Metrics, one of the world’s premier blockchain/cryptocurrency analytics firms, has updated its list of ‘trusted volume’ exchanges, adding a further five crypto exchanges, all the while adjusting scoring methods for trading platforms.

This time, FTX, Lbank, Liquid, The Rock Trading, and Upbit are joining the list that already features Coinbase, Bitfinex, and Binance.

Coin Metrics highlighted that those who didn’t make the ‘trusted volume’ list they just simply did not meet the parameters that had been set: “It is not to discredit any exchanges.”

“For example, this more conservative definition of trading volume can help institutions considering ETFs to more confidently gauge an asset’s daily spot trading volume for market sizing,” the firm said.

Other exchanges on the list include:

• Binance.us
• Bitbank
• bitFlyer
• Bitstamp
• Bittrex
• CEX.io
• Gate.io
• Gemini
• itBit
• Kraken

Initially, in July 2020, exchanges were ranked taking into account web traffic, trading volumes, developer tools, trading rules, and know-your-customer (KYC) standards. However, according to the firm, it didn’t quite quantify data as objectively as it could.

As such, Coin Metrics is making a few adjustments that have been based upon changes in the industry and community feedback.

This includes removing Western bias, including the volume of perpetual futures in their correlation tests, as well as tweaking the significance of web traffic data in their findings.

According to the firm, the element of Western bias has existed due to them taking a location-based approach to their assessments. To remedy this, Coin Metrics will observe daily trading volumes to iron out ‘seasonality differences’, as well as observing elements such as KYC, regulations, and trading rules independently of an exchanges’ legal residence.

With regards to perpetual futures being included, BitMEX, a major crypto derivatives exchange, was added to Coin Metrics ‘Benchmark Set’, as this further reduces analysis bias. Firstly, it does so by adding a data point that isn’t Western-centric, and secondly, it lowers other biases that may present themselves by adding “trading data related to liquidations and other related futures activities…”, thereby reducing the bias occurs against exchanges whose primary activities are found in futures.
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