Journal of the Korean Mathematical Society (대한수학회지)

Korean Mathematical Society (대한수학회)
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ROBUST PORTFOLIO OPTIMIZATION UNDER HYBRID CEV AND STOCHASTIC VOLATILITY

  • Cao, Jiling (Department of Mathematical Science School of Engineering Computer and Mathematical Sciences Auckland University of Technology) ;
  • Peng, Beidi (Department of Mathematical Science School of Engineering Computer and Mathematical Sciences Auckland University of Technology) ;
  • Zhang, Wenjun (Department of Mathematical Science School of Engineering Computer and Mathematical Sciences Auckland University of Technology)
  • Received : 2021.12.01
  • Accepted : 2022.08.17
  • Published : 2022.11.01
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Abstract

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity 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 optimal strategy and the first correction term with respect to various values of the model parameters.

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References

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