This paper looks into the Greek – Turkish arms race a decade after an earlier contribution on the issue that relied heavily on Artificial Neural Networks. The time period between the two papers contributes to the reliability of the results derived, not just by increasing the number of...

In recent years, the government, of African Countries has assumed major responsibilities for economic reforms and growth. In attempting to describe their economies, economists (policymakers) in many African Countries have applied certain models that are by now widely known: Linear programming...

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...

Murphy, Koehler, and Fogler [1997] gave in the last issue of the Journal of Portfolio Management an account of how to raise a neural net’s IQ. The purpose of this reply is to point out some of the general difficulties with neural nets. Also, I would like to mention an alternative method,...

This paper addresses the question of whether neural networks (NNs), a realistic cognitive model of human information processing, can learn to backward induce in a two-stage game with a unique subgame-perfect Nash equilibrium. The NNs were found to predict the Nash equilibrium approximately 70%...

According to theories of cultural neuroscience, Westerners and Easterners may have distinct styles of cognition (e.g., different allocation of attention). Previous research has shown that Westerners and Easterners tend to utilize analytical and holistic cognitive styles, respectively. On the...

This paper addresses how neural networks learn to play one-shot normal form games through experience in an environment of randomly generated game payoffs and randomly selected opponents. This agent based computational approach allows the modeling of learning all strategic types of normal form...