In this paper we use a Bayesian approach to test for mean reversion in the Swedish stock market on monthly data 1918-1998. By simply account for the heteroscedasticty of the data with a two state hidden Markov model of normal distributions and taking estimation bias into account via Gibbs...

In this paper we test for mean reversion in the Nordic stock markets using monthly nominal data 1947-1998. By simply account for the heteroscedasticity of the data with a regime-switching model of normal distributions and taking estimation bias into account via a Bayesian approach we can find no...

This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and...

This paper aims to evaluate if frictions in credit markets are important for business cycles in the U.S. and the Euro area. For this purpose, I modify the DSGE financial accelerator model developed by Bernanke, Gertler and Gilchrist (1999) by adding frictions such as price indexation to past...

The term "information risk" or "information uncertainty" is defined as the risk of a misleading signal. This risk is understood Bayesianly in terms of the likelihood function f(S|φ). In Bayesian method, f(S|φ) captures the quality of signal S with respect to parameter φ. The Bayesian position...

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities...