Abstract: The answer depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years. Even more accurate forecasts, however, are obtained when allowing the forecast combinations to vary across forecast horizons. While the latter approach is not always more accurate than selecting the single most accurate forecasting model by horizon, its accuracy can be shown to be much more stable over time. The MSPE of real-time pooled forecasts is between 3 % and 29 % lower than that of the no-change forecast and its directional accuracy as high as 73%. Our results are robust to alternative oil price measures and apply...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...
The paper examines the importance of combining high frequency financial information, along with the ...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...
Abstract: The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly...
We construct a monthly real-time dataset consisting of vintages for 1991.1-2010.12 that is suitable ...
We construct a monthly real-time dataset consisting of vintages for 1991.1-2010.12 that is suitable ...
We construct a monthly real-time data set consisting of vintages for 1991.1-2010.12 that is suitable...
Abstract: Forecasts of the quarterly real price of oil are routinely used by international organizat...
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts...
Expert outlooks on the future path of oil prices are often relied on by industry participants and po...
In recent years there has been increased interest in the link between financial markets and oil mark...
Expert outlooks on the future path of oil prices are often relied on by industry participants and po...
Little is known about the accuracy of expert outlooks, so heavily relied upon by industry participan...
Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine fo...
We address some of the key questions that arise in forecasting the price of crude oil. What do appli...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...
The paper examines the importance of combining high frequency financial information, along with the ...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...
Abstract: The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly...
We construct a monthly real-time dataset consisting of vintages for 1991.1-2010.12 that is suitable ...
We construct a monthly real-time dataset consisting of vintages for 1991.1-2010.12 that is suitable ...
We construct a monthly real-time data set consisting of vintages for 1991.1-2010.12 that is suitable...
Abstract: Forecasts of the quarterly real price of oil are routinely used by international organizat...
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts...
Expert outlooks on the future path of oil prices are often relied on by industry participants and po...
In recent years there has been increased interest in the link between financial markets and oil mark...
Expert outlooks on the future path of oil prices are often relied on by industry participants and po...
Little is known about the accuracy of expert outlooks, so heavily relied upon by industry participan...
Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine fo...
We address some of the key questions that arise in forecasting the price of crude oil. What do appli...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...
The paper examines the importance of combining high frequency financial information, along with the ...
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the ...