EconPapers    
Economics at your fingertips  
 

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
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2021.1965193 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:22:y:2022:i:3:p:481-500

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697688.2021.1965193

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:quantf:v:22:y:2022:i:3:p:481-500