Financial Machine Learning: Building a Dataset That Does Not Lie

Shuffled cross-validation reports 54 percent accuracy on market data containing no signal whatsoever, and that number is why competent machine learning so often fails on markets. This path fixes the dataset rather than the model: labels that describe trades someone would actually place, features that are stationary without being amnesiac, and a validation scheme that returns chance when there is nothing there. Every figure in it is computed and reproducible.