The Weak Efficient Market Hypothesis in Light of Statistical Learning

We make an unprecedented evaluation of statistical learning methods to forecast daily returns. Using a randomization test to adjust for data snooping, several models are found statistically significant on the tested equity indices: CSI 300, FTSE, and S&P 500. A best Sharpe ratio portfolio has abnormal returns on the S&P 500, breaking even with the market at 10 bps in round trip costs. The returns produce statistically significant intercept for factor regression models, qualifying as a new anomalous 3-day crisis persistency factor. These results open the path towards a standardized usage of statistical learning methods in finance.