DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management

By Kieran Wood, Stephen J. Roberts, Stefan Zohren

Published 2026-01-12

Everscope rating

1619.3

Relevance to quantitative trading

10 / 10

Implementation complexity

9 / 10

Reproducibility

3 / 5

About this paper

Methodology: DeePM (Deep Portfolio Manager). Problem types: Portfolio Optimization, Risk Management, Time Series Forecasting, Optimization, Reinforcement Learning, Graph Learning, Causal Inference.

arXiv:2601.05975 · Paper rankings

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