19.6 Recommended Literature

One for mathematicians, statisticians and economists well accessible introduction to the area of the neural network is, e.g., Refenes (1995a). Haykin (1999) offers a comprehensive and effective overview about different forms and applications of neural network. Anders (1997) introduces neural networks from econometrical and statistical view and discusses applications from the finance mathematical areas such as option pricing and insolvency prediction. Ripley (1996) discusses in detail the application of neural network to classification problems and puts them in respect with the classical discriminant analysis. Numerous practical applications of neural network in the finance area are introduced in Rehkugler and Zimmermann (1994), Refenes (1995b), Bol and Vollmer (1996) and Franke (2000). The application described in the previous section, calculating the Value at Risk by adaptation of a non-linear ARCHX process based on DAX stocks is described in Franke and Diagne (2002).