Pricing Power Options under the Heston Dynamics using the FFT

Pricing Power Options within the Heston Framework

Numerous studies have presented evidence that certain financial assets may exhibit stochastic volatility or jumps, which cannot be captured within the Black-Scholes environment. This work investigates the valuation of power options when the variance follows the Heston model of stochastic volatility. A closed form representation of the characteristic function of the process is derived from the partial differential equation (PDE) of the replicating portfolio. The characteristic function is essential for the computation of the European power option prices via the Fast Fourier Transform (FFT) technique. Numerical results are presented. © 2012 Published by NTMSCI Selection and/or peer review under responsibility of NTMSCI Publication Society

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  • Bastami, A. A., Belic, M. R., & Petrovic, N. Z. (2010). Special solutions of the Riccati equation with applications to the Gross-Pitaevskii nonlinear PDE. Electronic Journal of Differential Equations, 2010 (66), 1-10. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu.
  • Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, 637-659.
  • Boyle, P. P. (1977). Options: A Monte Carlo approach. Journal of Financial Economics, 4 (3), 323-338.
  • Carr, P., & Madan, D. (1999). Option valuation using the fast Fourier transform. Journal of Computational Finance, 2 (4), 61-73.
  • Esser, A. (2003). General valuation principles for arbitrary payoffs and applications to power options under stochastic volatility. Financial
  • Markets and Portfolio Management, 17 (3), 351-372. Gatheral, J. (2006). The Volatility Surface: A Practitioner's Guide. John Wiley and Sons.
  • Heston, S. L. (1993). A closed-form solution for options with stochastic volatility with applications to bond and currency options. Review of
  • Financial Studies, 6 (2), 327-343. Lord, R., Koekkoek, R., & van Dijk, D. (2010). A comparison of biased simulation schemes for stochastic volatility models. Quantitative Finance, 10 (2), 177-194.
  • Pillay, E., & O'Hara, J. G. (2011). FFT based option pricing under a mean reverting process with stochastic volatility and jumps. Journal of
  • Computational Applied Mathematics, 235 (12), 3378-3384.