We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results...

In this paper, we forecast energy market volatility using both univariate and multivariate GARCH-class models. First, we forecast volatilities of individual assets and find that multivariate models display better performance than univariate models. Second, we forecast crack spread volatility and...

We model daily catches of fishing boats in the Grand Bank fishing grounds. We use data on catches per species for a number of vessels collected by the European Union in the context of the Northwest Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a...

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results...

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty...

In this paper, we explore the strategy on hedging crude oil using refined product. We develop a regime switching asymmetric DCC (RS-ADCC) model by taking into account both of regime switching and asymmetry in correlations. Our out-of-sample findings indicate that RS-ADCC displays greater hedging...

In this paper, we forecast excess stock returns of S&P 500 index from January 1997 to December 2012 using both well-known traditional macroeconomic indicators and oil market variables. Based on a dynamic model selection approach, we find that the forecasting accuracy can be improved after adding...