数字加密货币
算法交易
波动性(金融)
技术分析
交易策略
金融市场
高频交易
计量经济学
结对贸易
金融经济学
经济
计算机科学
另类交易系统
财务
计算机安全
标识
DOI:10.1016/j.frl.2020.101655
摘要
This paper performs a reality check for the superior predictive ability of Machine Learning and Technical Analysis trading rules in the cryptocurrency market. After controlling for data snooping and various market frictions, we find that statistically significant positive excess returns are rarely achieved, independent of the data sampling frequency, type of trading position, or test significance level. Also, cross-sectional performance is correlated with risk factors such as beta and idiosyncratic volatility, implying that trading rules mostly capture market risk premiums. Overall, trading rules do not seem to provide additional benefits in cryptocurrency markets compared to traditional financial markets.
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