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Artificial Neural Network Enhanced Parametric Option Pricing

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Author Info
Panayiotis C. Andreou (University of Cyprus)
Chris Charalambous (University of Cyprus)
Spiros H. Martzoukos
Abstract

In this paper we explore ways that alleviate problems of nonparametric (artificial neural networks) and parametric option pricing models by combining the two. The resulting enhanced network model is compared to standard artificial neural networks and to parametric models with several historical and implied parameters. Empirical results using S\&P 500 index call options strongly support our approach.

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File URL: http://repec.org/sce2006/up.27825.1139911662.pdf
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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 118.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:118

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Related research
Keywords: Option pricing; implied volatilities; implied parameters; artificial neural networks; optimization;

Find related papers by JEL classification:
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

This paper has been announced in the following NEP Reports:

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