We investigate a parametric method for calibrating European option pricing using a Heston stochastic volatility model.We propose a numerical implementation scheme for calibrating a parameter set of the Heston stochastic volatility model through the particle swarm optimization
method to conquer the ill-posed inverse problem of the non-linear least squares and show that it can resolve the instability of the inverse problems. To verify the performance of the proposed method, we conduct simulations on some model-generated option prices and compare the performance with the Levenberg Marquardt method which is one of the popular nonlinear optimization method. We also use S& P 500 index option prices to check performances. The simulation results show that the proposed method has a better performance.
Key words: Option markets, Stochastic volatility models, Model calibration and selection, Particle Swarm optimization.
학회소식
학회소식
[2010년 제 2차] Robust Calibration of the Stochastic Volatility Mod
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2010-06-08
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