Extremum Options Pricing of Two Assets under a Double Nonaffine Stochastic Volatility Model

Shubin Ou, Guohe Deng and Petr H. Jek

Mathematical Problems in Engineering, 2023, vol. 2023, 1-20

Abstract: In this paper, we consider the pricing problem for the extremum options by constructing a double nonaffine stochastic volatility model. The joint characteristic function of the logarithm of two asset prices is derived by using the Feynman–Kac theorem and one-order Taylor approximation expansion. The semiclosed analytical pricing formulas of the European extremum options including option on maximum and option on minimum of two underlying assets are derived by using measure change technique and Fourier transform approach. Some numerical examples are provided to analyze the pricing results of extremum options under affine model, nonaffine model, Black–Scholes model, and the influences of some model parameters on the option. Numerical results show that the analytical pricing formulas have higher computational efficiency and accuracy than those of Monte Carlo simulation method. Also, results of sensitivity analysis report that the nonaffine models are more effective than other existing models in capturing the effect of volatility on option pricing.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1165629

DOI: 10.1155/2023/1165629

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