LSTM

I finally got an LSTM up and running, courtesy of the course Neural Networks in Trading from Quantinsti. So, just running their code, but it really isn’t much more complicated than an ordinary MLP. Also I’m warming to Tensorflow. It has some nice features such as saving the current best model as training progresses, and it appears to integrate well with scikit-learn, which has some pipeline related features that could be useful once things get more complex.

The above graph represents an interesting idea. The spread between predictions and actual value is plotted and trades using a mean reversion strategy. Bollinger Bands at 2 STD are shown. So many possibilities. I could include some version of an LSTM in an ensemble along with my XGBoost model and the (furure) RL model. Maybe I’ll find something that is consistently profitable some day after all.