Dexin Peng, Xiaoyu Wang · 2026 · SSRN Electronic Journal
DOI: 10.2139/ssrn.7528558 · cited by 0 works (OpenAlex) · open-access PDF
Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existing empirical asset pricing literature provides strong benchmarks for shallow models. Residual learning allows neural network models in asset pricing to go deeper by preserving and refining their shallow counterparts. The out-of-sample Sharpe ratio for value-weighted long-short portfolios of deep residual models (2.07) is higher than that for the corresponding shallow ones (1.92) and more than twice that of the deep feedforward models (0.89). We sh
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Topics: Capital asset pricing model, Residual, Consumption-based capital asset pricing model, Asset (computer security), Arbitrage pricing theory, Econometrics
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