Residual Learning in Empirical Asset Pricing
The research tested if deeper neural networks using residual learning improve asset pricing performance. By comparing standard models to residual models, the study found that deeper architectures generate significant economic value in out-of-sample portfolio returns. This proves that incorporating residual connections allows models to better refine stock rankings and outperform shallower versions.