Reinforcement Learning for Risk-Sensitive Investment Management: a Free Energy–Entropy Duality Approach

By Sébastien Lleo, Wolfgang Runggaldier

Published 2026-06-23

Everscope rating

1863.5

Relevance to quantitative trading

9 / 10

Implementation complexity

8 / 10

Reproducibility

3 / 5

About this paper

Methodology: Continuous-time q-learning actor–critic via Free Energy–Entropy Duality. Problem types: Portfolio Optimization, Reinforcement Learning, Risk Management, Stochastic Control, Stochastic Differential Games, Continuous-Time Optimization.

arXiv:2606.20903 · Paper rankings

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