stock prediction : GRU model predicting same given values instead of future stock price

Question

i was just testing this model from kaggle post this model suppose to predict 1 day ahead from given set of last stocks. After tweaking few parameters i got

Answer 1

In my opinion this is happening because your loss function here is mean squared error. The best way to minimize this error is by using the previous value as the estimate for the current step (especially if the steps are nearby).

You will start seeing the limitations of your model clearly if you try to predict the delta between samples.

I am currently experiencing similar issues trying to predict using time series. I haven't found a solution yet, but am working on extracting features as others pointed out.

Answer 2

It is a well-known issue with regression actually. Since the task of the regressor is to minimize error, it secures it task by choosing the closest value from the features you input to the regressor. It becomes the case especially in the time-series problems.

1) Never give unprocessed closing value that you want your model to predict, especially in the time-series regression problems. More generally, never give a feature that gives some direct numerical intuition to a regressor about what the label might be.

2)If you are not sure whether the model just replicates like your case, be sure to plot the original test set and your prediction all together to visually analize the situation. Moreover, if you can, do a simulation of your model on the real-time data to observe whether your model predicts with the same performance.

3)I’d recommend you to apply binary classification rather than regression.

I’ve been intensely working on financial signal prediction for nearly a year, do not hesitate to ask more.

Have fun.