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Improving the pricing of options: a neural network approach

โœ Scribed by Ulrich Anders; Olaf Korn; Christian Schmitt

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
299 KB
Volume
17
Category
Article
ISSN
0277-6693

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โœฆ Synopsis

In this paper we apply statistical inference techniques to build neural network models which are able to explain the prices of call options written on the German stock index DAX. By testing for the explanatory power of several variables serving as network inputs, some insight into the pricing process of the option market is obtained. The results indicate that statistical speciยฎcation strategies lead to parsimonious networks which have a superior out-of-sample performance when compared to the Black/Scholes model. We further validate our results by providing plausible hedge parameters.

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