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Optimal Transport for Continuous-Time Mean-Variance Portfolio Selection
Abstract
The continuous-time mean-variance portfolio selection problem is investigated in this paper through a rigorous integration of backward stochastic differential equation (BSDE) and Kantorovich duality theory. We propose a novel analytical framework for addressing feedback control in McKean-Vlasov stochastic systems. By solving three coupled systems of ordinary differential equations (ODEs), we derive an explicit, closed-loop optimal feedback investment strategy.
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BibTeX
@misc{zeng2026optimal,
title = {{Optimal Transport for Continuous-Time Mean-Variance Portfolio Selection}},
author = {Yijie Zeng and Liangquan Zhang and Xun Li},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.18398},
eprint = {2610.18398},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.18398},
}
RIS
TY - UNPB
TI - Optimal Transport for Continuous-Time Mean-Variance Portfolio Selection
AU - Yijie Zeng
AU - Liangquan Zhang
AU - Xun Li
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2610.18398
UR - https://arxiv.org/abs/2610.18398
AB - The continuous-time mean-variance portfolio selection problem is investigated in this paper through a rigorous integration of backward stochastic differential equation (BSDE) and Kantorovich duality theory. We propose a novel analytical framework for addressing feedback control in McKean-Vlasov stochastic systems. By solving three coupled systems of ordinary differential equations (ODEs), we derive an explicit, closed-loop optimal feedback investment strategy.
ER -