The paper studies the problem of maximizing the expected utility of terminal wealth in the framework of a general incomplete semimartingale model of a financial market. We show that the necessary and sufficient condition on a utility function for the validity of several key assertions of the...

We introduce a very simple but efficient idea for branch & bound (B&B) algorithms in global optimization (GO). As input for our generic algorithm, we need an upper bound algorithm for the GO maximization problem and a branching rule....

In this paper we analyze the evolution of output decisions of adaptive firms in an environment of oligopolistic competition. The firm might either choose to produce one of several existing product variants or try to establish a new product variant on the market....

This paper presents first results from research into open source projects from a software engineering perspective. The research methodology employed relies on public data retrieved from the CVS-repository of the GNOME project and relevant discussion groups.(...)

Okun's Law postulates an inverse relationship between movements of the unemployment rate and the real gross domestic product (GDP). Empirical estimates for US data indicate that a two to three percent GDP growth rate above the natural or average GDP growth rate causes unemployment to decrease by...

In this paper we investigate the potential of the analysis of noisy non-stationary time series by quantizing it into streams of discrete symbols and applying finite-memory symbolic predictors. The main argument is that careful quantization can reduce the noise in the time series to make model...

Aufbauend auf einem klassischen Finanzmarktmodell behandeln wir drei Modellvarianten, die jeweils einen anderen Ansatz der (heterogenen) Erwartungsbildung von Investoren über künftige Wertpapierpreise in den Vordergrund der Betrachtungen rücken: das Konzept der konsistenten Erwartungen, das...

In this paper we propose an unsupervised voting-merging scheme that is capable of clustering data sets, and also of finding the number of clusters existing in them. The voting part of the algorithm allows us to combine several runs of clustering algorithms resulting in a common partition.(...)

The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also...