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European Option Pricing by Using the Support Vector Regression Approach

  • Panayiotis C. Andreou
  • Chris Charalambous
  • Spiros H. Martzoukos
Conference paper
  • 1.2k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5768)

Abstract

We explore the pricing performance of Support Vector Regression for pricing S&P 500 index call options. Support Vector Regression is a novel nonparametric methodology that has been developed in the context of statistical learning theory, and until now it has not been widely used in financial econometric applications. This new method is compared with the Black and Scholes (1973) option pricing model, using standard implied parameters and parameters derived via the Deterministic Volatility Functions approach. The empirical analysis has shown promising results for the Support Vector Regression models.

Keywords

Option pricing implied volatility non-parametric methods support vector regression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Panayiotis C. Andreou
    • 1
  • Chris Charalambous
    • 2
  • Spiros H. Martzoukos
    • 2
  1. 1.Durham UniversityUK
  2. 2.University of CyprusCyprus

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