Models of Artificial Foreign Exchange Markets

this paper, we focus on a specific financial system, the so-called Foreign Exchange Market. We first review its main rules and describe its most notable properties. Then, we propose a simple model (a market microsimulation) aimed at reproducing the behavior of each actor in such a market (traders, banks,...). Numerical simulations show that this model captures several of the qualitative features of the real market, as the results of the interaction of many actors. 2 B. Chopard and R. Chatagny Finally, we give some indications on how we could improve our results. Our main purpose is not to make financial predictions but, rather, to understand how complexity builds up from the aggregation of many individual behaviors. 2. THE FOREIGN EXCHANGE MARKE

Foreign exchange trading using a learning classifier system

We apply a simple Learning Classifier System to a foreign exchange trading problem. The performance of the Learning Classifier System is compared to that of a Genetic Programming approach from the literature. The simple Learning Classifier System is able to achieve a positive excess return in simulated trading, but results are not yet fully competitive because the Learning Classifier System trades too frequently. However, the Learning Classifier System approach shows potential because returns are obtained with no offline training and the technique is inherently adaptive, unlike many of the machine learning methods currently employed for financial trading. © 2008 Springer-Verlag Berlin Heidelberg

Genetically diabetic animals.

Several animal species, mostly rodents, were described to exhibit spontaneously diabetes mellitus on a hereditary basis. These findings were highly appreciated with the expectation to get more insight into the pathogenesis of diabetes in humans. During the last few years since the discovery of leptin (Zhang et al. 1994) and its downstream signal transduction cascade (Friedman and Halaas 1998), tremendous new insight of the genetics of diabetic and obese animal disease models was derived. Up to now, at least six genetically diabetic animal models exhibit defects in the leptin pathway: the ob mutation in the mouse resulted in leptin deficiency. The db mutation in the mouse and the cp and fa mutations in the rat are different mutations of the leptin receptor gene. The fat mutation in the mouse results in a biologically inactive carboxypeptidase E, which processes the prohormone conversion of POMC into α-MSH, which activates the hypothalamic MC4 receptor. Finally the Agouti yellow (y) mouse exhibit a ubiquitous expression of the Agouti protein which represents an antagonist of the hypothalamic MC4 receptor