This is my first post related to my topic course in investment strategies. The goal is to find out the most relevant factors to predict returns. I will be updating this post in the next days.
Thanks, Omar that's very helpful research with using ScikitLearn AdaBoostClassifier - I find the "Overnight Returns" attribution quite useful.
Are you looking to explore "Weekly Returns" attribution - expectedly the factors ranking are quite different - as well?
@Alan and @Karl thanks a lot for commenting and sorry for replying late. Please feel free to make any suggestions that would improve the results or calculation of factors.
@ Karl i am currently trying to study the predictive power of different factors of overnight, intraday and first/last 30 minutes returns.
Great work, Omar!
I wonder how if that could feed into Grant Kiehne's post on multi-factor weights equation:
alpha = wc_0*(w_0*alpha_0 + w_3*alpha_3 + w_4*alpha_4) + wc_1*(w_1*alpha_1 + w_2*alpha_2)
I understand that this may be way off course from your ML topic :o)
@Karl i am not sure how exactly the SpectralClustering function that he is using here works. but maybe one could apply it to the the results we get from our pipeline and then include it as an extra factor that will be fed to the classifier to see the predictive power of this kind of weighted clustering ? or maybe analyze the combined alpha with alphalens ?
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