Trading System phigh/plow etc about alphapy HOT 2 OPEN

is any update on this?

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Yes, you are correct that the model trains on a group of stocks, according to the list of stocks in your market.yml file. This trained model does not apply to just a single stock, but the entire group as well when making predictions. If you just need to train for a single instrument, then you would just have a single stock in the market configuration file. For example, I do this with cryptocurrency data where BTC is the only symbol, thus the probabilities apply only to BTC.

But I do see your point. Currently, if you have a group for training, then we do not train individually on each component and then apply each independent model for prediction. This is an extremely important point for aggregated models in general. For example, if I develop a neural network tuner for one car, can I apply that model to another car? Probably not. But then you have to consider that stock behavior changes over time and consequently you have two options. Is it better to retrain each single-component model on a periodic basis, or do you have a general-purpose model that holds up historically across instruments? I don't know if many people have the answers for this.

Thank you for your thoughts, and further discussion is welcome!

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