Weak convergence of utility-risk portfolios
File(s)URweakconv.pdf (445.26 KB)
Accepted version
Author(s)
Wong, Kwok Chuen
Yam, Sheung Chi Phillip
Yang, Hailiang
Zheng, Harry
Type
Journal Article
Abstract
In this article, we establish the validity of the Donsker invariance principle for weak convergence of the optimal utility-downside-risk portfolio payoff. Thus, the optimal solution is robust to changes in the market model via the pricing kernel. The convergence result is valid for all feasible combinations of utility functions satisfying the Inada conditions, convex downside deviation risk measures, and pricing kernels satisfying integrability conditions. Thus, our results provide a unified framework to understand whether utility-downside-risk solutions are stable under mild misspecifications of asset price processes. As another application, we further obtain a result that the optimal utility-risk values and policies driven by discrete-time binomial models converge weakly to those of the limiting continuous-time Black-Scholes model. We demonstrate the convergence result using numerical examples and find that the optimal utility-risk value converges as the time interval of the binomial model gets smaller.
Date Issued
2025-09-01
Date Acceptance
2025-08-01
Citation
Mathematical Control and Related Fields, 2025
ISSN
2156-8472
Publisher
American Institute of Mathematical Sciences
Journal / Book Title
Mathematical Control and Related Fields
Volume
0
Issue
0
Copyright Statement
Copyright © 2025 American Institute of Mathematical Sciences. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Subjects
DISCRETE
downside deviation risk
MANAGEMENT
Mathematics
Mathematics, Applied
MODEL
nonlinear moment problem
OPTIMAL CONSUMPTION
OPTIMIZATION
Physical Sciences
POLICIES
portfolio risk management
Portfolio selection
Science & Technology
SELECTION
semivariance
Publication Status
Published online
Date Publish Online
2025-09-01