Reinforcement Learning and Stochastic Optimization in Multi-Asset Portfolio Construction: A Data-Driven Investment Framework

Authors

  • Marko Bohanec Associate Professor of Computer Science, University of Ljubljana

Keywords:

reinforcement learning, stochastic optimization, multi-asset portfolio construction, data-driven investment framework, machine learning

Abstract

Artificial intelligence (AI) today is critical in portfolio optimization. Since the 1960s, technology has become a significant part of investing. The way investment managers generate outperformance has completely changed. Advancements in big data, machine learning, and AI have allowed managers to uncover innovative ways for the detection of valuable insights that human capability could not do so easily.

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Published

30-06-2026

How to Cite

[1]
“Reinforcement Learning and Stochastic Optimization in Multi-Asset Portfolio Construction: A Data-Driven Investment Framework”, Adv. in Deep Learning Techniques, vol. 6, no. 1, pp. 10–18, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/adlt/article/view/777