In this paper we apply statistical inference techniques to build neural network models which are ahle 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, same 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 cornpared to the Black/Scholes model. We further validate our results by providing plausible hedge parameters.
Anders, U., O. Korn and C. Schmitt (1996), Improving the Pricing of Options. A Neutral Network Approach, ZEW Discussion Paper No. 96-04, Mannheim. Download