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
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.