数学季刊 ›› 2025, Vol. 40 ›› Issue (1): 59-73.doi: 10.13371/j.cnki.chin.q.j.m.2025.01.006

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具有Markov转换的双因素随机波动率跳扩散模型下幂期权定价

  

  1. College of Mathematics and Statistics, Guangxi Normal University, Guilin 541006, China
  • 收稿日期:2024-04-08 出版日期:2025-03-30 发布日期:2025-03-30
  • 通讯作者: 韦煜明 E-mail:ymwei@gxnu.edu.cn
  • 作者简介:HAN Shu-shu (1999-), female, native of Kaizhou, Chongqing, master degree student of Guangxi Normal University, engages in financial economics; WEI Yu-ming (1974-), male, native of Guiping, Guangxi, professor of Guangxi Normal University, engages in financial economics.
  • 基金资助:
    Guangxi Natural Science Foundation (Grant No. 2023GXNSFAA026246).

Power Options Pricing under Markov Regime-Switching Two-Factor Stochastic Volatility Jump-Diffusion Model

  1. College of Mathematics and Statistics, Guangxi Normal University, Guilin 541006, China
  • Received:2024-04-08 Online:2025-03-30 Published:2025-03-30
  • Contact: WEI Yu-ming E-mail:ymwei@gxnu.edu.cn
  • About author:HAN Shu-shu (1999-), female, native of Kaizhou, Chongqing, master degree student of Guangxi Normal University, engages in financial economics; WEI Yu-ming (1974-), male, native of Guiping, Guangxi, professor of Guangxi Normal University, engages in financial economics.
  • Supported by:
    Guangxi Natural Science Foundation (Grant No. 2023GXNSFAA026246).

摘要: In this paper, we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options. Furthermore, we assume that the interest rates and the jump intensities of the assets are stochastic. Under the proposed framework, first, we derive the analytical pricing formula for power options by using Fourier transform technique, Esscher transform and characteristic function. Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation. Finally, we provide some sensitivity analysis of the model parameters to power options. Numerical examples show this model is suitable for empirical work in practice.

关键词: Power options, Markov regime-switching, Stochastic volatility, Stochastic interest rate, Stochastic intensity

Abstract: In this paper, we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options. Furthermore, we assume that the interest rates and the jump intensities of the assets are stochastic. Under the proposed framework, first, we derive the analytical pricing formula for power options by using Fourier transform technique, Esscher transform and characteristic function. Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation. Finally, we provide some sensitivity analysis of the model parameters to power options. Numerical examples show this model is suitable for empirical work in practice.

Key words: Power options, Markov regime-switching, Stochastic volatility, Stochastic , interest rate, Stochastic intensity

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