In this paper, I develop an algorithm for solving heterogeneous agent dynamic models in which individual decision rules influence each other. This approach is more general than the other heterogeneous agent solution methods in that it only requires a well formed objective function. The key...

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...

We analyze the learning behaviour of a Simple Genetic Algorithm in an overlapping generations model with one consumption good and fiat money. It is shown by simulations, that in cases where periodic equilibria exist the equilibrium of period two is learned by a Genetic Algorithm and not the...

Resources for construction activities are limited in the real construction world. To avoid waste and shortage of resources on a construction jobsite, scheduling must include resource allocation. A new resourceconstrained construction scheduling system is proposed in this paper. A GA-based...

Resources for construction activities are limited in the real construction world so that scheduling must include resource allocation. Furthermore, activity duration is uncertain due to the variation in the outside environment, such as resource availabilities, weather, space congestion, etc. A...

This paper presents a methodology for simulation optimization utilizing genetic algorithms and applies it to a newly developed simulation-based system for estimating the time and cost of earthmoving operations. The genetic algorithm searches for a near-optimum fleet configuration that reduces...

We present an investment process that: (i) decomposes securities into risk factors; (ii) allows for the construction of portfolios of assets that would selectively expose the manager to desired risk factors; (iii) perform a risk allocation between these portfolios, allowing for tracking error...