77% Of Trading Volumes on Unregulated Exchanges Is Wash Trading: NBER Report

77% Of Trading Volumes on Unregulated Exchanges Is Wash Trading

With exchanges still the focus amid the FTX fallout, a new report by the National Bureau of Economic Research reveals that three in four transactions in unregulated crypto exchanges are bogus. 

In the research paper titled “Crypto Wash Trading,” authors Lin William Cong, Xi Li, Ke Tang, and Yang Yang studied 29 exchanges, including Huobi, Coinbase, and Binance, using statistical tools and behavioral patterns to determine fraudulent transactions. 

“We find that the wash trading volume, on average, is as high as 77.5% of the total trading volume on unregulated exchanges, with a median of 79.1%. In particular, wash trades on the twelve Tier-2 exchanges are estimated to be more than 80% of the total trade volume,” wrote the researchers. 

These volumes accounted for $4.5 trillion in spot markets and over $1.5 trillion in derivatives markets in Q1 of 2020. 

According to the paper, the biggest factors fueling wash trading are short-term incentives. 

Firstly, transaction volumes directly impact the rankings of exchanges on data and analytics sites such as Coinmarketcap. “70% of wash trading of total reported volume moves an exchange’s rank up by 46 positions.” Secondly, an exchange’s trading volume is positively correlated with the price of its native cryptocurrency. 

As a result, wash trading on lesser-known exchanges is much more prominent than on established exchanges. Smaller exchanges have a larger incentive to drive growth without attracting too much attention. 

On the other hand, regulated exchanges have committed considerable resources to prevent wash trading as they face severe punishments for market manipulation. 

The researchers conclude that the findings of the study underline the importance of regulations in emerging industries, “using wash-trading-adjusted volume in certain empirical studies” and “using statistical tools and behavioral benchmarks for forensic finance and fraud detection.”

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