This paper evaluates the profitability of applying four different volatility forecastingmodels to the trading of straddles on the German stock market index DAX. Special carehas been taken to use simultaneous…
In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests,information criteria and cross validation. The application of these methods in…
Various empirical studies have shown that the time-varying volatility of asset returns can be described by GARCH (generalised autoregressive conditional heteroskedasticity) models. The corresponding GARCH option…
The Value at Risk approach (VaR) is more and more used as a tool for risk measurement. The approach however has shortcomings both from a theoretical and a practical point of view. VaR can be classified within…
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…