One of most promising applications of wavelets is in the field of nonparametric statistical estimation, in which one wants to estimate an unknown signal from some noisy data. Donoho and Johnstone (1994) have developed a simple and yet powerful methodology for nonparametric regression and...

Capital budgeting textbooks usually consider the financial perspective to be the most important, or even the only perspective that should be considered in project evaluation. However, there are often certain factors that cannot be incorporated in the financial value of a project and that are...

Genetic programming (or GP) is a random search technique that emerged in the late 1980s and early 1990s. A formal description of the method was introduced in Koza (1992). GP applies to many optimization areas. One of them is modeling time series and using those models in forecasting. Unlike...

We present the algorithm OPTGAME 2.0 to solve N-person discrete-time LQ games exactly, and discrete-time non-linear quadratic games approximately by means of an appropriate linearization procedure, where N2. I.e., the objective function is assumed to be quadratic in the deviations of states and...

A model has been developed to study the interdependence between the choice of information technology and industry structure. Advances in information technology might provide incentives for a firm to specialize or focus on its core competence. However, the degree of specialization depends on the...

The paper analyzes the effects of individual--specific and economy--wide productivity shocks on intertemporal decision--making of risk averse agents. We focus especially on the consequences for long--run growth. By contrasting the most widely used models of modern growth theory, namely the...

FGP (Financial Genetic Programming) is a genetic programming based system that specialises in financial forecasting. In the past, we have reported that FGP-1 (the first version of FGP) is capable of producing accurate predictions in a variety of data sets. It can accurately predict whether a...

A portfolio management problem is approximated through a Markov decision chain. The weak Euler scheme is applied to discretise the time evolution of a portfolio and an inverse distance method is used to describe the transition probabilities. The approximating Markov decision problem is solved by...

We propose a general scenario to analyze technological changes in socio-economic environments. We illustrate the ideas with a model that incorporating the main trends is simple enough to extract analytical results and, at the same time, sufficiently complex to display a rich dynamic behavior....

The paper considers a dynamic macroeconomic model with stochastic quantity rationing. The economy is composed of overlapping-generations consumers, producers and a government who interact in a labor and a consumption goods market. Agents behave optimizing and trade in each period, even when...