The use of neural networks trained by a new hybrid algorithm is employed on forecasting the Greek Foreign Exchange-Rate Market. Four major currencies, namely the U.S. Dollar (USD), the Deutsche Mark (DEM), the French Franc (FF) and the British Pound (GBP), versus the Greek Drachma, were used as...

I present an undetermined coefficients method for obtaining a linear approximating to the solution of a class of dynamic, rational expectations models. I also show how that solution can be used to compute a model's implications for impulse response functions and for second moments. Copyright...

We describe methods for solving general linear rational expectations models in continuous or discrete timing with or without exogenous variables. The methods are based on matrix eigenvalue decompositions. Copyright 2002 by Kluwer Academic Publishers

It is important for financial institutions to develop methods to predict their exposure and keep their risk under control. Portfolio managers can insure themselves against the value (of a diversified stock portfolio) dropping below a certain level, by holding in conjunction with the stock...

The paper studies the dynamics of market prices under the assumption of behavioural learning by sellers and buyers. The buyers are assumed to be price takers who learn about choosing sellers and acceptable prices, whilst the sellers have the possibility to offer a fixed price or to make...

Under general conditions, linear decision rules of agents with rational expectations are equivalent to restricted error corrections. However, empirical rejections of rational expectation restrictions are the rule, rather than the exception, in macroeconomics. Rejections often are conditioned on...

We use game theory and Santa Fe Artificial Stock Market, an agent-based model of an evolving stock market, to study the optimal frequency for traders to revise their market forecasting rules. We discover two things: There is a unique strategic Nash equilibrium in the game of choosing forecast...