Calibrating Option Pricing Models with Heuristics

  • Manfred Gilli
  • Enrico Schumann
Part of the Studies in Computational Intelligence book series (SCI, volume 380)

Summary

Calibrating option pricing models to market prices often leads to optimisation problems to which standard methods (such as those based on gradients) cannot be applied.We investigate two models: Heston’s stochastic volatility model, and Bates’s model which also includes jumps. We discuss how to price options under these models, and how to calibrate the parameters of the models with heuristic techniques.

Keywords

Particle Swarm Optimisation Differential Evolution Option Price Stochastic Volatility Implied Volatility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Manfred Gilli
    • 1
  • Enrico Schumann
    • 2
  1. 1.University of GenevaSwitzerland
  2. 2.VIP Value Investment ProfessionalsZugSwitzerland

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