shahgem / cind-820 Goto Github PK

I was looking for this kind of research and just found your repo and you actively working on it.

Did you consider training the LSTM model on all tokens that are offered on a specific crypto exchange at once? I'm curios if this would have any effect on the accuracy as one could assume that the money mostly stays in the exchange meaning the tokens influence each other.

The endgoal would be to not predict if a token goes up or done but to predict which token will increase the most in the selected timeframe.

The trading process could be one trade per day and it switches to the token the model predicts will have the highest increase in closing price - for simplicity the model could be trained on the same time period one plans to trade on - like training on daily time frame, the model would have to identify which of the used coins will most likely have the highest increase in the next bar/day.

As you are currently doing research in this field could I ask you to give me your opinion on this approach?