Ridgeless regression augmented with noise predictors achieves oracle-level asymptotic forecast accuracy in latent-factor economic models by shrinking design matrix eigenvalues.
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Cross-sectional dispersion in firm-level realized skewness negatively predicts future aggregate stock market returns and is strongest in months with monetary policy news.
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Benign Overfitting in Economic Forecasting via Noise Regularization
Ridgeless regression augmented with noise predictors achieves oracle-level asymptotic forecast accuracy in latent-factor economic models by shrinking design matrix eigenvalues.