On Cost-Sensitive Distributionally Robust Log-Optimal Portfolio

Autor:	Hsieh, Chung-Han, Yu, Xiao-Rou
Rok vydání:	2024
Předmět:	Mathematics - Optimization and Control Electrical Engineering and Systems Science - Systems and Control Quantitative Finance - Computational Finance Quantitative Finance - Portfolio Management 91G10 93E03 90C17 90C46 90C25
Druh dokumentu:	Working Paper
Popis:	This paper addresses a novel \emph{cost-sensitive} distributionally robust log-optimal portfolio problem, where the investor faces \emph{ambiguous} return distributions, and a general convex transaction cost model is incorporated. The uncertainty in the return distribution is quantified using the \emph{Wasserstein} metric, which captures distributional ambiguity. We establish conditions that ensure robustly survivable trades for all distributions in the Wasserstein ball under convex transaction costs. By leveraging duality theory, we approximate the infinite-dimensional distributionally robust optimization problem with a finite convex program, enabling computational tractability for mid-sized portfolios. Empirical studies using S\&P 500 data validate our theoretical framework: without transaction costs, the optimal portfolio converges to an equal-weighted allocation, while with transaction costs, the portfolio shifts slightly towards the risk-free asset, reflecting the trade-off between cost considerations and optimal allocation. Comment: Submitted for possible publication
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.23536 Zobrazit plný text záznamu View this record from Arxiv