Accelerating the calibration of stochastic volatility models
Fiodar Kilin
No 6, CPQF Working Paper Series from Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF)
Abstract:
This paper compares the performance of three methods for pricing vanilla options in models with known characteristic function: (1) Direct integration, (2) Fast Fourier Transform (FFT), (3) Fractional FFT. The most important application of this comparison is the choice of the fastest method for the calibration of stochastic volatility models, e.g. Heston, Bates, Barndorff-Nielsen-Shephard models or Levy models with stochastic time. We show that using additional cache technique makes the calibration with the direct integration method at least seven times faster than the calibration with the fractional FFT method.
Keywords: Stochastic Volatility Models; Calibration; Numerical Integration; Fast Fourier Transform (search for similar items in EconPapers)
JEL-codes: G13 (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cpqfwp:6
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