Not sure how I feel about de prado. For some things they are just stupid, like what the fuck is triple barrier and other times they are genius. Like when he said t-values of microstructure features. He did a meh job on the explanation, and I prefer Hasbrouck's book, but GOAT idea
Anyways, have a skim through advanced is financial machine learning and tell for yourself. There are a few moments of genius and other times utter horseshit. Fractional differencing is genius, but it isn't explained properly and the stationarity of features etc is key.
some features do not need stationarity, a lot of them don't. Most wavelets need stationarity, but modern methods have non-stationary wavelets now! Here is a lecture by him I mildly agreed with:
A very passive-aggressive review from me, but I do think he has some amazing ideas, but there is a great deal of filtering needed to ingest it, and I do recommend you implement the ideas, test them skeptically, and then do further reading elsewhere like microstructure.
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