I'm quite new to Quantopian and I'm exploring the possibility of use machine learning for my algorithms. I started with an admittedly naive notebook to see if I can find and linear correlation between some fundamental factors and the quarterly returns.
As I developed and tested this notebook I started to have both financial and coding doubts where I'm sure you can point me in the right direction:
- To normalize values and avoid outliers I used the equity relative rank of the factor instead of the absolute value. How reasonable do you think is this approach?
- For all factors I found an R^2 in my linear regression very low (always below 0.1). Is my approach incorrect or simply there is no obvious, linear correlation between these common factors and the returns?
- Any way to improve the pipeline performance? Is it possible to run it monthly instead of daily?
I also hope this could be a useful structure for any other person playing around with fundamental factors.
Thank you in advance for your help!