随机因素模型中的鲁棒效用最大化

IF 1.3 Q2 STATISTICS & PROBABILITY
D. Hernández-Hernández, A. Schied
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引用次数: 76

摘要

摘要本文给出了不完全市场模型鲁棒效用最大化问题解的显式PDE表征,该模型的波动率、利率过程和长期趋势由外部随机因素过程驱动。鲁棒效用函数是根据HARA效用函数定义的,该效用函数具有负风险厌恶和动态一致的连贯风险度量,这允许资产价格动态和因素过程分布中的模型不确定性。我们的方法结合了最优投资理论的两个最新进展:鲁棒效用最大化的一般对偶理论和确定最优鞅度量的对偶问题的随机控制方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust utility maximization in a stochastic factor model
SUMMARY We give an explicit PDE characterization for the solution of a robust utility maximization problem in an incomplete market model, whose volatility, interest rate process, and long-term trend are driven by an external stochastic factor process. The robust utility functional is defined in terms of a HARA utility function with negative risk aversion and a dynamically consistent coherent risk measure, which allows for model uncertainty in the distributions of both the asset price dynamics and the factor process. Our method combines two recent advances in the theory of optimal investments: the general duality theory for robust utility maximization and the stochastic control approach to the dual problem of determining optimal martingale measures.
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来源期刊
Statistics & Risk Modeling
Statistics & Risk Modeling STATISTICS & PROBABILITY-
CiteScore
1.80
自引率
6.70%
发文量
6
期刊介绍: Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.
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