# Bayesian Optimization for CVaR-based portfolio optimization

arXiv: https://arxiv.org/abs/2503.17737 · HTML: https://mlsanity.com/paper/2503.17737/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Mar 2025.

## Built on by (most cited first, 2 of 2)

- [Trust Region Constrained Bayesian Optimization with Penalized Constraint Handling](https://mlsanity.com/paper/2603.24567/) (2026)
- [Bayesian Optimization of CVaR with Unknown Hyperparameters](https://mlsanity.com/paper/2610.18306/) (2026)

## Abstract (arXiv)

Optimal portfolio allocation is often formulated as a constrained risk problem, where one aims to minimize a risk measure subject to some performance constraints. This paper presents new Bayesian Optimization algorithms for such constrained minimization problems, seeking to minimize the conditional value-at-risk (a computationally intensive risk measure) under a minimum expected return constraint. The proposed algorithms utilize a new acquisition function, which drives sampling towards the optimal region. Additionally, a new two-stage procedure is developed, which significantly reduces the number of evaluations of the expensive-to-evaluate objective function. The proposed algorithm's competitive performance is demonstrated through practical examples.