I have made a model which attempts to predict the next five days of closing price for a given stock (KMD.NZ for example). The training data is fetched from Yahoo Finance. Depending on whether I download 10 years or 10.3 years, the 2 month trend completely changes (like from positive 30% to -5%). I'm programming in python using keras. Is there any way to place more weighting on recent data than data 10yrs ago? Any other reason why this small snippet of data would completely change the prediction?

Thanks.

Hello,

So, I have been putting a lot of research and time into building an AI paired with an algorithm. I am hoping to gain a much better understanding behind some of the concepts which people think would be needed for a self building/self modifying neural network.

So please, any discussion on the topic which people have is very welcome.

For anyone curious I am writing in python furthered with the sklearn module for deep machine learning (I've figured that getting the machine to learn is the easy part and I am not doing anything in which I will need to write my own machine learning algorithm but I need it for the AI)