Power utility maximization with expert opinions at fixed arrival times in a market with hidden Gaussian drift
Publication date
2024-08-11
Document type
Forschungsartikel
Author
Organisational unit
Publisher
Springer Science+Business Media
Series or journal
Annals of Operations Research
ISSN
Periodical volume
341
Periodical issue
2-3
First page
897
Last page
936
Is referenced by
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Abstract
In this paper we study optimal trading strategies in a financial market in which stock returns depend on a hidden Gaussian mean reverting drift process. Investors obtain information on that drift by observing stock returns. Moreover, expert opinions in the form of signals about the current state of the drift arriving at fixed and known dates are included in the analysis. Drift estimates are based on Kalman filter techniques. They are used to transform a power utility maximization problem under partial information into an optimization problem under full information where the state variable is the filter of the drift. The dynamic programming equation for this problem is studied and closed-form solutions for the value function and the optimal trading strategy of an investor are derived. They allow to quantify the monetary value of information delivered by the expert opinions. We illustrate our theoretical findings by results of extensive numerical experiments.
Description
This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
Version
Published version
Access right on openHSU
Metadata only access
Open Access Funding
Springer Nature (DEAL)