mlsanityData to 7 Oct 2026

Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization

arXiv 2403.07916 ↗First posted 27 Feb 2024cs.AI cs.LGcited by 4

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Abstract (arXiv)

This research paper delves into the application of Deep Reinforcement Learning (DRL) in asset-class agnostic portfolio optimization, integrating industry-grade methodologies with quantitative finance. At the heart of this integration is our robust framework that not only merges advanced DRL algorithms with modern computational techniques but also emphasizes stringent statistical analysis, software engineering and regulatory compliance. To the best of our knowledge, this is the first study integrating financial Reinforcement Learning with sim-to-real methodologies from robotics and mathematical physics, thus enriching our frameworks and arguments with this unique perspective. Our research culminates with the introduction of AlphaOptimizerNet, a proprietary Reinforcement Learning agent (and corresponding library). Developed from a synthesis of state-of-the-art (SOTA) literature and our unique interdisciplinary methodology, AlphaOptimizerNet demonstrates encouraging risk-return optimization across various asset classes with realistic constraints. These preliminary results underscore the practical efficacy of our frameworks. As the finance sector increasingly gravitates towards advanced algorithmic solutions, our study bridges theoretical advancements with real-world applicability, offering a template for ensuring safety and robust standards in this technologically driven future.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 59 of its 146 references that are in the map. First posted on arXiv 27 Feb 2024.

Builds on

59 of 146 references.

References · 59

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38 more
  1. 2021Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learningcited by 157
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50 most cited of 59 All 59 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Large-scale portfolio optimization with variational neural annealingcited by 0
  2. 2025Robust Reinforcement Learning in Finance: Modeling Market Impact with Elliptic Uncertainty Setscited by 0
  3. 2026Agentic AI for Self-Driving Laboratories in Soft Matter: Taxonomy, Benchmarks,and Open Challengescited by 0
  4. 2026Deep Reinforcement Learning for Reliability Based Bi-Objective Portfolio Optimizationcited by 0