Introduction. The objects of investigation of this work are micro-level behaviors in stock markets. We aim at better understanding which strategies of market participants drive stock markets. The problem is that micro-level data from real stock markets are largely unobservable. We take an...

This research studies possible existence of business cycle asymmetries in Canada, France, Germany, Italy, Japan, UK, and US real GDP growth rates. Asymmetries in these countries are modeled using in-sample as well as jackknife out-of-sample forecasts approximated from artificial neural networks....

In this paper the application of Arbitrage Pricing Theory (APT) and multifactorial pricing is studied on the Swiss stock market. In order to estimate the factors used in the multifactorial model, it is proposed to use the new method of Independent Component Analysis. This method laying on neural...

Human forecasting capacity is still very limited. In spite of the extreme efforts of specialists in several different areas for years developing scientific knowledge, forecasting various events, such as climatic conditions at a given time, the evolution of a commodity price in the future, remain...

This paper introduces a neural-net approach to perform discriminant analysis in business research. A neural net represents a nonlinear discriminant function as a pattern of connections between its processing units. Using bank default data, the neural-net approach is compared with linear...

Предсказание финансовой неустойчивости компании является дискуссионной темой в экономической литературе и остается таковой уже на протяжении многих лет....

In this position paper we discuss how language influences the mind by comparing robots that have language with robots that do not have language. Robots with language respond more adaptively to objects belonging to different categories and requiring different behaviors compared to robots without...

We use an ecosystem simulator capable of evolving arbitrary neural network topologies to explore the relationship between an information theoretic measure of the complexity of neural dynamics and several graph theoretical metrics calculated for the underlying network topologies. Evolutionary...

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...

Regression and neural network models of wage determination are constructed where the explanatory variables include detailed information about the impact of school curricula on future earnings. It is established that there are strong nonlinearities and interaction effects present in the...