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arXiv · 2602.19204

CBO algorithm with average drift and applications to portfolio optimization

Hyeong-Ohk Bae·Seung-Yeal Ha·Chanho Min·Jane Yoo·Jaeyoung Yoon
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Abstract

We propose a consensus based optimization algorithm with average drift (in short Ad-CBO) and provide a theoretical framework for it. In the theoretical analysis, we show that particle solutions to Ad-CBO converge to a global minimizer. In numerical simulations, we examine Ad-CBO's performance in optimizing static and dynamic objective functions. As a real-time application, we test the efficiency of Ad-CBO to find the optimal portfolio given stochastically evolving multi-asset prices in a financial market. The proposed Ad-CBO exhibits higher searching speed, lower tracking errors and regret bound than the CBO without stochastic diffusion

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Hyeong-Ohk Bae, Seung-Yeal Ha, Chanho Min, Jane Yoo, Jaeyoung Yoon. 2026-02-22. CBO algorithm with average drift and applications to portfolio optimization. https://arxiv.org/abs/2602.19204

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