Excuse my ignorance with this I am still trying to wrap my head around the interpretation of the Fama French 1992 factor paper.
I come from a computer science background but I am interested in applying myself to finance also.
My question is could some machine learning models (ANN, SVM etc.) be applied to the CAPM model/FF 3 factor model, for example;
1) Find more optimal portfolios for the FF 3 factor model (instead of just having size sorted and High Book to Market sorted portfolios would it be possible to use machine learning to find portfolios of firms with similar-firm level characteristics and ask a neural network to go out and find the "best" characteristics to sort on a portfolio.
In an academic sense could it be enough to use ML to create a new factor portfolio?
2) Could it also be possible to estimate excess returns of an asset through machine learning methods?
ActualAssetReturn = RskFreeRate + B(ExpectedMktReturn - RskFreeRate)
Are people applying NN or other ML methods to the above equation?
Is it plausable to pass through a deep neural network DNN inputs of the risk free rate, expected market return and Beta estimates (from OLS) to obtain predicted values for Asset returns? train it on an in-sample dataset and test on an out-of-sample data set...
Again excuse my ignorance I am still studying this stuff but would like to clear up one or two things I am unsure about.