Multi-basin particle swarm intelligence method for optimal calibration of parametric Lévy models

Authors:
Seungho Yang;Jaewook Lee
Affiliations:
Department of Industrial and Management Engineering, Pohang University of Science and Technology (POSTECH), San 31 Hyoja, Pohang 790-784, South Korea;Department of Industrial Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-744, South Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

In this paper, we propose a novel intelligent method to improve the calibration quality of parametric exponential Levy models that have recently emerged as alternative option pricing models. The method based on so-called multi-basin systems consists of three sequential phases to expedite the search for a good parameter set and to reduce the burden of selecting proper initial set of particles for particle swarm intelligence techniques. We conduct simulations on model-generated option prices and real data of option prices to verify the performance of the proposed method and show that the method can significantly improve the calibration quality in a systematic and automatic way.