Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimization

By Giovanni Dispoto, Marcello Restelli, Carmine Ventre

Published 2026-09-02

Everscope rating

1460.5

Relevance to quantitative trading

8 / 10

Implementation complexity

8 / 10

Reproducibility

3 / 5

About this paper

Methodology: Multi-Objective Reinforcement Learning with Gaussian Process Preference Elicitation. Problem types: Portfolio Optimization, Reinforcement Learning, Multi-objective Optimization, Preference Elicitation, Active Learning.

arXiv:2609.02677 · Paper rankings

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