A comprehensive introduction to how ML can add value to the design and execution of algorithmic trading strategies
View the Project on GitHub stefan-jansen/machine-learning-for-trading
Lopez de Prado and Bailey (2014) also derive a deflated SR to compute the probability that the SR is statistically significant while controlling for the inflationary effect of multiple testing, non-normal returns, and shorter sample lengths.
The script deflated_sharpe_ratio contains the commented implementation made available by Marcos Lopez de Prado on his website.