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A path integral approach to closed-form option pricing formulas with applications to stochastic volatility and interest rate models

Author

Listed:
  • D. Lemmens
  • M. Wouters
  • J. Tempere
  • S. Foulon

Abstract

We present a path integral method to derive closed-form solutions for option prices in a stochastic volatility model. The method is explained in detail for the pricing of a plain vanilla option. The flexibility of our approach is demonstrated by extending the realm of closed-form option price formulas to the case where both the volatility and interest rates are stochastic. This flexibility is promising for the treatment of exotic options. Our new analytical formulas are tested with numerical Monte Carlo simulations.

Suggested Citation

  • D. Lemmens & M. Wouters & J. Tempere & S. Foulon, 2008. "A path integral approach to closed-form option pricing formulas with applications to stochastic volatility and interest rate models," Papers 0806.0932, arXiv.org.
  • Handle: RePEc:arx:papers:0806.0932
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    File URL: http://arxiv.org/pdf/0806.0932
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    Cited by:

    1. Lemmens, D. & Liang, L.Z.J. & Tempere, J. & De Schepper, A., 2010. "Pricing bounds for discrete arithmetic Asian options under Lévy models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5193-5207.
    2. Bustamante, M. & Contreras, M., 2016. "Multi-asset Black–Scholes model as a variable second class constrained dynamical system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 540-572.
    3. Zura Kakushadze, 2014. "Path Integral and Asset Pricing," Papers 1410.1611, arXiv.org, revised Aug 2016.
    4. Anantya Bhatnagar & Dimitri D. Vvedensky, 2022. "Quantum effects in an expanded Black–Scholes model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(8), pages 1-12, August.
    5. Grillo, Sebastian & Blanco, Gerardo & Schaerer, Christian E., 2015. "Path integration for real options," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 120-132.
    6. Contreras, Mauricio & Pellicer, Rely & Villena, Marcelo, 2017. "Dynamic optimization and its relation to classical and quantum constrained systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 12-25.
    7. Zura Kakushadze, 2015. "Path integral and asset pricing," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1759-1771, November.
    8. Contreras G., Mauricio, 2014. "Stochastic volatility models at ρ=±1 as second class constrained Hamiltonian systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 289-302.
    9. G., Mauricio Contreras & Peña, Juan Pablo, 2019. "The quantum dark side of the optimal control theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 450-473.
    10. Capuozzo, Pietro & Panella, Emanuele & Schettini Gherardini, Tancredi & Vvedensky, Dimitri D., 2021. "Path integral Monte Carlo method for option pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    11. Axel A. Araneda & Marcelo J. Villena, 2018. "Computing the CEV option pricing formula using the semiclassical approximation of path integral," Papers 1803.10376, arXiv.org.

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