This paper applies the model confidence sets (MCS) procedure to a set of volatility models. A MSC is analogous to a confidence interval of parameter in the sense that the former contains the best forecasting model with a certain probability. The key to the MCS is that it acknowledges the...

In this paper we present a forecasting method for time series using copula-based models for multivariate time series. We study how the performance of the predictions evolve when changing the strength of the different possible dependencies, as well as the structure of the dependence. We also look...

In view of the failure of high profile companies like Circuit City and Linens n Things, Financial distress or bankruptcy prediction has generated much interest recently. This research develops and tests a model for the prediction of bankruptcy of retail firms. We use accounting variables such as...

We consider the basic problem of refi tting a time series over a finite period of time and formulate it as a stochastic dynamic program. By changing the underlying Markov decision process we are able to obtain a model that at optimality considers historical data as well as forecasts of future...

The contribution of this paper is to show how the balance of risk for various macro variables can be linked to inflation uncertainty. Inflation uncertainty is derived from uncertainty in the macro variables that are deemed to be important for future inflation. The paper focuses on the technical...

This paper provides a new approach to recover relative entropy measures of contemporaneous dependence from limited information by constructing the most entropic copula (MEC) and its canonical form, namely the most entropic canonical copula (MECC). The MECC can effectively be obtained by...