Determinants of wash trading in major cryptoexchanges
研究了2020年11月至2022年1月四种主流加密货币的交易所洗盘交易，发现市场波动和公众情绪是主要驱动因素，并提供了识别和缓解此类行为的工具，对监管者和投资者有参考价值。
We investigate a crypto-market-wide phenomenon of wash trading that affects exchange integrity and the accuracy of liquidity claims. We examine four leading cryptocurrencies using a dataset that spans from November 15, 2020, to January 31, 2022. We employ two detection approaches to assess the extent of wash trading: a trade-size roundness metric and a Benford’s law-based deviation metric. We examine more than 40 different explanatory variables, including blockchain and cryptocurrency measures, as well as financial and macroeconomic factors. Variable selection is conducted using a robust combination of the variance inflation factor and Bayesian model averaging. Our findings indicate that market volatility and public sentiment are robustly associated with wash trading, with its volume tending to rise under volatile conditions on which exchanges may capitalize. The models in our study provide valuable insights for regulators and market participants in identifying and mitigating such practices, thereby enhancing market integrity and investor confidence. • We quantify wash trading for Bitcoin, Ethereum, Litecoin, and XRP. • We use trade volume roundness and Benford’s law-based detection metrics. • Market volatility and public sentiment are major determinants. • Exchanges exploit volatile conditions to expand wash-trading volume. • Bayesian model averaging identifies robust wash trading predictors.