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arXiv Machine Learning By Hui Guo, Jiawei Huang, Runze Li, Yan Yu

(Mis)Understanding Benign Overfitting in Equity Return Prediction

Read the original on arXiv Machine Learning →

The paper examines whether benign overfitting—where highly overparameterized models still predict well—occurs in equity return prediction. It finds a double‑descent risk curve for ridgeless models and shows that while ridge regularization slightly improves performance, the advantage vanishes at high parameter‑to‑observation ratios. Ultimately, both models fail to beat a simple historical average, indicating that standard equity predictors lack genuine forecasting power even with flexible machine learning methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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