A Markov Chain Monte Carlo method is proposed for the pointwise evaluation of a density whose normalizing constant is not known. This method was introduced in the physics literature by Assaraf et al (2007). Conditions for unbiasedness of the estimator are derived. A central limit theorem is also...

We propose a Bayesian nonparametric model to estimate rating migration matrices and default probabilities using the reinforced urn processes (RUP) introduced in Muliere et al. (2000). The estimated default probability becomes our prior information in a parametric model for the prediction of the...

We empirically investigate the predictive power of the various components affecting correlations that have been recently introduced in the literature. We focus on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover,...

Based on the APARCH model and two outlier detection methods, we computereliable time series of volatility asymmetry for 49 countries with relatively few ob-servations. Results show a steady increase in the asymmetry over the years for mostcountries. We nd that economic development and market...

This paper determines the value of asset tradeability in an option pricing framework.In our model, tradeability is valuable since it allows investors to exploit temporary mis-pricings of stocks. The model delivers several novel insights on the value of tradeability:The value of tradeability is...

Demand is growing for a better understanding of how assets are priced in countries outside of the U.S.While financial data are available for many firms world-wide, it is important to have a reliable andreplicable method of constructing high-quality systematic risk factors from these data. This...