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Anders, Ulrich
Korn, Olaf
Schmitt, Christian
Year of Publication: 
Series/Report no.: 
ZEW Discussion Papers 96-04
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 input variables serving as network inputs, some insight into the pricing process of the option market is obtained. The results indicate that statistical specification 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.
Option Pricing
Neural Networks
Statistical Inference
Model Selection
Document Type: 
Working Paper

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