Abstract: The S&P500 is difficult to predict. Multi-factor models provide a useful framework for making returns predictions and for controlling portfolio risk. This paper explores a three-step process in predicting PCA and Autoencoders factors to generate multi-factor models from the S&P500 component securities.
finance
linear-regression
pca-analysis
autoencoders
autoregressive
sp500
autoregressive-moving-average
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Updated
Jan 18, 2020 - HTML