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. --...

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.

In this note we explore the following surprising fact: In regression with trend and seasonality, the prediction risk is constant for all seasons of a new cycle, despite the fact that it increases with time when the seasons are left out. Awareness of this may be useful to both the practicing...

In this paper, we discuss discrete choice theory and show how this theory can be used to quantify learning effects in experimental studies. We argue why the ordering quantities in newsvendor experiments should follow a multinomial logit distribution. We provide a robustness analysis to explain...