Robust control in a rough environment
Bingyan Han and
Hoi Ying Wong
Quantitative Finance, 2022, vol. 22, issue 3, 481-500
Abstract:
This paper studies robust decision problems in a rough environment that is described by Volterra processes. Various alternative dominated models are introduced to reflect decision makers' concerns regarding model uncertainty. Using a functional Itô calculus approach, we characterize the robust optimal strategy by a path-dependent Hamilton–Jacobi–Bellman–Isaacs equation. Explicit strategies are derived for robust power and exponential utility maximization with the Volterra Heston model and an example from a robust linear-quadratic control problem. Numerical study shows that it becomes harder to distinguish two probability measures in a rougher environment. Robust optimal investment strategies can reduce losses from ignoring volatility roughness and model uncertainty and can improve the stability of portfolio performance.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:22:y:2022:i:3:p:481-500
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DOI: 10.1080/14697688.2021.1965193
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