I fixed all the bugs in the code that uses a DDQN to make trading decisions for ADA/USDT. I learned some important things such as how to properly use the gather method in PyTorch. Seems the error that was giving me the most trouble (and which caused me to research said gather method) was due to my specifying that my network had 2 outputs when it should have had 3. My bad, but a good lesson learned. Also, must admit that the results look promising. However in the past every trading strategy that ‘looked promising’ ended up losing me money, so I’m not going to fall for that again.
ETA: I haven’t done any validation on that promising backtest result, so it really doesn’t mean much. I’ll have to grab some more recent data and test out the model on that to see if it actually generalizes instead of overfitting the training data. Still, I might be a lot closer to Phases 3 and 4 of my plan than I realized in my last post.