OPTIMAL INVESTMENT UNDER PARTIAL INFORMATION AND ROBUST VAR-TYPE CONSTRAINT

Nicole Bã„uerle and An Chen ()
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Nicole Bã„uerle: Department of Mathematics, Karlsruhe Institute of Technology, D-76128 Karlsruhe, Germany
An Chen: Institute of Insurance Science, University of Ulm, Helmholtzstrasse 20, D-89069 Ulm, Germany

International Journal of Theoretical and Applied Finance (IJTAF), 2023, vol. 26, issue 04n05, 1-18

Abstract: This paper extends the utility maximization literature by combining partial information and (robust) regulatory constraints. Partial information is characterized by the fact that the stock price itself is observable by the optimizing financial institution, but the outcome of the market price of the risk 𠜃 is unknown to the institution. The regulator develops either a congruent or distinct perception of the market price of risk in comparison to the financial institution when imposing the Value-at-Risk (VaR) constraint. We also discuss a robust VaR constraint in which the regulator uses a worst-case measure. The solution to our optimization problem takes the same form as in the full information case: optimal wealth can be expressed as a decreasing function of state price density. The optimal wealth is equal to the minimum regulatory financing requirement in the intermediate economic states. The key distinction lies in the fact that the price density in the final state depends on the overall evolution of the estimated market price of risk, denoted as 𠜃̂(s) or that the upper boundary of the intermediate region exhibits stochastic behavior.

Keywords: Uncertainty about drift; value-at-risk-based regulation; risk management (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219024923500176

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