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Mar 9

Calibrating Stochastic Volatility Models with Heuristic Techniques

Posted by abiao at 10:45 | Code » Matlab | Comments(0) | Reads(10814)
Stochastic volatility models, specifically, Heston model, SABR model, are introduced before and become the widely used among academia and industry. However, the calibration process is difficult because generally the pricing requires numerical integration, and calibration requires to find five and eight parameters instead of only one for Black Scholes model.

Found a paper Calibrating Option Pricing Models with Heuristics, where the author look into the calibration of Heston (1993) and Bates (1996) models. Finding parameters that make the models consistent with market prices means solving a non-convex optimisation problem. Optimisation heuristics is suggested for this issue, more specifically they show that Differential Evolution and Particle Swarm Optimisation are both able to give good solutions to the problem.

Take a look if you are interested, in the Appendix the R and Matlab codes are given for a better understanding. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1566975

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