I’m already questioning my decision from the previous post, to focus on Unsupervised Learning. In the back of my mind is the advice from Ernie Chan, that ML is most useful for metalabelling – deciding whether to trade (or not) where actual signals have come from a non-ML strategy. I guess this is a supervised classification problem. My new book on Unsupervised Learning has started with a chapter on Supervised Learning, which is what has reminded me of all this.
What I’m actually thinking of is some kind of weird hybrid system, where a classification of ‘good time to trade’ is in fact a buy signal for whatever data feed into the trained model. So combining strategy with metalabelling. What could go wrong?