This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test...

Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR). We provide a comprehensive look at the problem by considering...

This paper develops a Bayesian vector autoregressive model(BVAR) for the leader of the Portuguese car market to forecast the market share. The model includes five marketing decision variables.The Bayesian prior is selected on the basis of the accuracy of the out-of-sample forecasts. We find that...