Options Pricing Via Statistical Learning Techniques: The Support Vector Regression Approach

25 Pages Posted: 16 Jun 2008  

Panayiotis C. Andreou

Cyprus University of Technology

Christakis Charalambous

University of Cyprus - Department of Public and Business Administration

Spiros Martzoukos

University of Cyprus - Department of Public and Business Administration; George Washington University - School of Business

Date Written: June 2008

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 been practically neglected in financial econometric applications. This new method is compared with Parametric Options Pricing Models using standard implied parameters and parameters derived via Deterministic Volatility Functions. The empirical analysis has shown promising results for the Support Vector Regression approach.

Keywords: Option pricing, implied volatilities, implied parameters, deterministic volatility functions, support vector machines, neural networks

JEL Classification: G13, G14

Suggested Citation

Andreou, Panayiotis C. and Charalambous, Christakis and Martzoukos, Spiros, Options Pricing Via Statistical Learning Techniques: The Support Vector Regression Approach (June 2008). Available at SSRN: https://ssrn.com/abstract=1145329 or http://dx.doi.org/10.2139/ssrn.1145329

Panayiotis C. Andreou (Contact Author)

Cyprus University of Technology ( email )

School Of Management and Economics
P.O. Box 50329
Lemesos, 3036
Cyprus

HOME PAGE: http://www.pandreou.com

Christakis Charalambous

University of Cyprus - Department of Public and Business Administration ( email )

75 Kallipoleos Street
P.O. Box 20537
Nicosia CY-1678
CYPRUS
00357-2-892258 (Phone)
00357-2-339063 (Fax)

Spiros Harilaos Spiridon Martzoukos

George Washington University - School of Business

Washington, DC 20052
United States
202-994-5996 (Phone)
202-994-5014 (Fax)

University of Cyprus - Department of Public and Business Administration ( email )

75 Kallipoleos Street
P.O. Box 20537
Nicosia CY-1678
CYPRUS
357-2-892474 (Phone)
357-2-892460 (Fax)

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