This paper addresses the notion that many fractional I(d) processes may fall into the ?empty box? category, as discussed in Granger (1999). We present ex ante forecasting evidence based on an updated version of the absolute returns series examined by Ding, Granger and Engle (1993) that suggests...

This paper outlines testing procedures for assessing the relative out-of-sample predictive accuracy of multiple conditional distribution models. The tests that are discussed are based on either the comparison of entire conditional distributions or the comparison of predictive confidence...

ERP Systems are developed to assist information management and analysis to organisations for gaining business advantage. Although ERP systems claim to produce competitive advantage for companies investing on ERP, it is still questionable (See [9]: Powell, 1997). This is also valid for IT in...

In the past, researches have used statistical, operational research or simulation techniques, in finding solutions to improve management systems. In contrast to these procedures, we introduce a new way of integrating operations research and statistics to build an Operational Statistics Model and...

Asymptotic inference on nonstationary fractional time series models, including cointegrated ones, is proceeding along two routes, determined by alternative definitions of nonstationary processes. We derive bounds for the mean squared error of the difference between (possibly tapered) discrete...

Our answer: Not so well. We reached that conclusion after reviewing recent research on the role of technology as a source of economic fluctuations. The bulk of the evidence suggests a limited role for aggregate technology shocks, pointing instead to demand factors as the main force behind the...

The paper analyzes foreign exchange market volatility in four Central European EU accession countries in 2001-2003. By using a Markov regime-switching model, it identifies two regimes representing high- and low-volatility periods. The estimation results show not only that volatilities are...

This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it...