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autoregressive-moving-average

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Leo8216 / An-Analysis-of-PCA-and-Autoencoder-Generated-Factors-in-Predicting-SP500-Returns

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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
  • Updated Jan 18, 2020
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