Robust optimal asset-liability management with mispricing and stochastic factor market dynamics

被引:4
|
作者
Wang, Ning [1 ]
Zhang, Yumo [2 ]
机构
[1] Macquarie Univ, Macquarie Business Sch, Dept Actuarial Studies & Business Analyt, Sydney, NSW 2109, Australia
[2] Univ Copenhagen, Dept Math Sci, Univ Pk 5, Copenhagen 2100, Denmark
来源
基金
中国国家自然科学基金;
关键词
Asset-liability management; Model ambiguity; Mispricing; Stochastic factor; Backward stochastic differential equation; VARIANCE PORTFOLIO SELECTION; OPTIMAL INVESTMENT STRATEGY; VOLATILITY MODEL; MEAN-REVERSION; INTEREST-RATES; REINSURANCE; RISK; AMBIGUITY; CHOICE; INFLATION;
D O I
10.1016/j.insmatheco.2023.09.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper investigates a robust optimal asset-liability management problem under an expected utility maximization criterion. More specifically, the manager is concerned about the potential model uncertainty and aims to seek the robust optimal investment strategies. We incorporate an uncontrollable random liability described by a generalized drifted Brownian motion. Also, the manager has access to an incomplete financial market consisting of a risk-free asset, a market index with potentially path-dependent, time-varying risk premium and volatility, and a pair of mispriced stocks. The market dynamics are assumed to rely on an affine-form, square-root factor process and the price error is modeled by a co-integrated system. We adopt a backward stochastic differential equation approach hinging on the martingale optimality principle to solve this non-Markovian robust control problem. Closed-form expressions for the robust optimal investment strategies, the probability perturbation process under the well-defined worst-case scenario and the corresponding value function are derived. The admissibility of the robust optimal controls is verified under some technical conditions. Finally, we perform some numerical examples to illustrate the effects of model parameters on the robust investment strategies and draw some economic interpretations from these results.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页码:251 / 273
页数:23
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