We consider a financial market model with a large number of interacting agents. Investors are heterogeneous in their expectations about the future evolution of an asset price process. Their current expectation is based on the previous states of their "neighbors" and on a random signal about the...

We study the long run behaviour of interactive Markov chains on infinite product spaces. The behaviour at a single site is influenced by the local situation in some neighborhood and by a random signal about the average situation throughout the whole system. The asymptotic behaviour of such...

We study the long run behaviour of interactive Markov chains on infinite product spaces. In view of microstructure models of financial markets, the interaction has both a local and a global component. The convergence of such Markov chains is analyzed on the microscopic level and on the...

We develop a nonparametric estimation theory in a non-stationary environment, more precisely in the framework of null recurrent Markov chains. An essential tool is the split chain, which makes it possible to decompose the times series under consideration in independent and identical parts. A...

We consider a financial market model with interacting agents and study the long run behaviour of both aggregate behaviour and equilibrium prices. Investors are heterogeneous in their price expectations and they get stochastic signals about the "mood" of the market described by the empirical...

Most of the empirical studies dealing with international business cycles have disregarded the credibility issues that play an important role in the decision to join or not a monetary union. Most of empirical applications based on asymmetric shocks have failed to account for these aspects. In...

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods. --...

We consider a diffusion model of small variable type with positive drift density varying in a nonparametric set. We investigate Gaussian and Poisson approximations to this model. In the sense of asymptotic equivalence of experiments, it is shown that observation of the diffusion process until...