deepm
Unverified ML strategy on Multi by kieranjwood. BotFinder score 18 out of 100.
This code accompanies the paper DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management (https://arxiv.org/abs/2601.05975)
Source: github
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deepm
DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management Paper | PDF Kieran Wood, Stephen J. Roberts, Stefan Zohren All of our works are covered on my website. This repository contains the code to reproduce the experiments in the paper. We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three fundamental challenges in financial learning: (1) it resolves the asynchronous "ragged filtration" problem via a Directed Delay (Causal Sieve) mechanism that prioritizes causal impulse-response learning over information freshness; (2) it combats low signal-to-noise ratios via a Macroeconomic Graph Prior, regularizing cross-asset dependence according to economic first principles; and (3) it optimizes a distributionally robust objective where a smooth worst-window penalty serves as a differentiable proxy for Entropic Value-at-Risk (EVaR) — a window-robust utility encouraging strong performance in the most adverse historical subperiods. In large-scale backte
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