oil futures prices, exchange rates of particular countries and stock-market indexes. Out-of-sample forecasting results …, they generally lose their forecasting power at higher forecast horizons. The results also suggest that exchange rates help …, and fınds that forecast averaging significantly improves the forecasting performances …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is … at 1-step ahead. -- Exchange rates ; Forecasting ; Bayesian VAR …

policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a …

. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that …

. While the forecasting error of the combined forecast tends to be systematically smaller than that of the individual model …

heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 … ability (SPA) test, we evaluate and compare their forecasting performance at short and long horizons. The empirical results …. However, the new MSM model comes out as the model that most often across forecasting horizons and subsamples cannot be …

-ahead forecasting horizons relative to the short memory GARCH specification. Additionally, the results suggest that underestimation of … the true VaR figure becomes less prevalent as the forecasting horizon increases. Furthermore, the GARCH model has a lower … forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …