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Numerical methods applied to option pricing models with transaction costs and stochastic volatility

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  • Maria C. Mariani
  • Indranil SenGupta
  • Granville Sewell

Abstract

In this paper, we solve a complex partial differential equation motivated by applications in finance where the solution of the system gives the price of European options, including transaction costs and stochastic volatility. The model is based on theoretical analysis, and the resulting differential equation is solved using PDE2D software. The stability analysis agrees well with experimental results.

Suggested Citation

  • Maria C. Mariani & Indranil SenGupta & Granville Sewell, 2015. "Numerical methods applied to option pricing models with transaction costs and stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1417-1424, August.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:8:p:1417-1424
    DOI: 10.1080/14697688.2015.1032548
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    Cited by:

    1. Yipeng Yang & Allanus Tsoi, 2016. "A Level Set Analysis and A Nonparametric Regression on S&P 500 Daily Return," IJFS, MDPI, vol. 4(1), pages 1-24, February.
    2. Yan, Dong & Lin, Sha & Hu, Zhihao & Yang, Ben-Zhang, 2022. "Pricing American options with stochastic volatility and small nonlinear price impact: A PDE approach," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    3. Daniel Suescún-Díaz & Luis Eduardo Girón, 2023. "Valuation of Standard Call Options Using the Euler–Maruyama Method with Strong Approximation," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1545-1560, April.

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