Neural networks (NN) and fuzzy logic systems (FLS) are used successfully for financial forecasting, credit rating and portfolio management. In search for more sophisticated modeling techniques a mixture of NN and FLS has proved to be worth consideration. We propose the novel constructive...

We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. A feature that makes this family particularly desirable for econometric applications is that it possesses closed-form expressions for its anti-derivatives (e.g., the...

The literature on electoral cycles has developed in two distinct phases. The first one considered the existence of non-rational (naive) voters whereas the second one considered fully rational voters. In our perspective, an intermediate approach is more interesting, i.e. one that considers...

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...

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 neural network models is discussed, paying attention especially to the identification...

Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of...

The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the...

In this article we evaluate the pricing performance of the rather simple but revolutionary Black-Scholes model and one of the more complex techniques (neural networks) on the European-style S&P Index call and put options over the period of 1.6.2006 till 8.6.2007. Our results on call options show...

This paper addresses new trends in quantitative geography research. Modern social science research - including economic and social geography - has in the past decades shown an increasing interest in micro-oriented behaviour of actors. This is inter alia clearly reflected in spatial interaction...

In this paper we try to put together both the dynamics of the endogenous evolution of an industry and the corresponding dynamics on the capital market. The first module of our modelling efforts is the endogenous evolution of the industry based on the micro-behaviour of boundedly rational agents....