> The key problem with their analysis is that they don't do a proper train-test split. Yes, that's bad. But the enterprise is doomed even earlier than that: th

> The key problem with their analysis is that they don't do a proper train-test split. Yes, that's bad. But the enterprise is doomed even earlier than that: the author is using a naive regression technique on timeseries data. Stock price data is typically log-normally distributed and non-stationary. If the author is not going to use a robust timeseries technique like ARIMA, they need to transform and constrain the data to account for non-stationarity. Otherwise it's trivial to find superfluous correlations which appear to show a strong linear relationship between some fundamental financial metric and some other technical indicator, because both may have a temporal component (e.g. stocks tend to go up over time, and a lot of technical indicators have some implicit component which also increase or decrease with time). This is also why it's important to have a strong fundamental thesis to explain what's going on.