ROBUST PORTFOLIO OPTIMIZATION UNDER HYBRID CEV AND STOCHASTIC VOLATILITY

被引:0
|
作者
Cao, Jiling [1 ]
Peng, Beidi [1 ]
Zhang, Wenjun [1 ]
机构
[1] Auckland Univ Technol, Dept Math Sci, Sch Engn Comp & Math Sci, Auckland, New Zealand
关键词
Asymptotic approximation; exponential utility; HJB equation; optimal strategy; robust; SVCEV model; PENSION-PLANS; CONSUMPTION; TESTS; RULES;
D O I
10.4134/JKMS.j210728
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we investigate the portfolio optimization prob-lem under the SVCEV model, which is a hybrid model of constant elas-ticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading op-timal strategy and the first correction term with respect to various values of the model parameters.
引用
收藏
页码:1153 / 1170
页数:18
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