The development and use of dynamic optimization model is extremely important in financial markets. The classical mean-variance portfolio model assumes the expected returns are known with perfect precision. In practice, however, it is extremely difficult to estimate precisely. While portfolios...

The mixture of two already known soft computing technics, like Genetic Algorithms and Neural Networks (NN) in Financial modeling, takes a new approach in the search for the best variables involving an Econometric model using a Neural Network. This new approach helps to recognice the importance...

This paper deals with artificial agents buying and selling products in a virtual market of goods that may be substituted for each other. On the demand side the market features a homogenous group of agents whose dynamics are determined by three different scenarios. The supply side, on the other...

In this paper, an agent-based computational capital asset pricing model is applied to address an issue, known as the elasticity puzzle, originating from a famous reciprocal relation between the elasticity of intertemporal substitution (EIS) and the relative risk aversion (RRA) coefficient. By...

Mathematically oriented microeconomic research has contributed enormously to the understanding of economic behavior and the functioning of markets and institutions. However, theoretical as well as applied microeconomic studies may be driven too much by mathematical feasibility. An illustrative...