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Fig 5 was incorrectly included and should be omitted. In the APT strategy subsection of the Empirical analysis, there are errors in the second paragraph. The correct paragraph is: We classify stocks into two categories: upward potential stocks (undervalued stocks) and downward potential stocks (overvalued stocks), based on a comparison of their expected returns with actual returns.
PLOS ONE, Jul 2023 This study analyzes the explanatory power of the latent factor conditional asset pricing model for the Korean stock market using an autoencoder. The autoencoder is a type of neural network in machine learning that can extract latent factors. Specifically, we apply the conditional autoencoder (CA) model that estimates factor exposure as a flexible nonlinear function of covariates. Our main findings are as follows.
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