arXiv Machine Learning July 28, 2026 By Yu-Chen Den, Kuan-Yu Chen, Kendro Vincent, Tien-Hao Chang

MAPLE: Efficient and Diverse Multi-Alpha Generation for Portfolio Construction

Read the original on arXiv Machine Learning →

arXiv:2607. 24131v1 Announce Type: new Abstract: Classical alpha mining achieves strong risk-adjusted returns by combining many low-correlated predictive signals, yet deep learning stock-ranking methods typically produce a single alpha per stock, rely on increasingly complex architectures with diminishing gains, and obtain diversity only through separate models or implicit routing, without explicitly controlling inter-alpha correlation.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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