Abstract
We examine whether new factors have explanatory power for the cross-section of expected returns compared to existing factors. Machine-learning-based double-selection LASSO determines pricing factors explaining the cross-section in the Korean stock market. Among the recently proposed factors in the factor zoo, gross profitability exhibits significant SDF loadings, as confirmed by robustness checks. We suggest that significant factors can vary across markets.
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