Real-time forecast combinations for the oil price
Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine forecasts from six empirical models to predict real oil prices.In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real‐time variables. Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real-time variables. futures, and (iii) RAC, (iv) WTI, and (v) Brent oil price forecasts from the Short-Term Energy Outlook published by the U.S. Energy Information Administration (EIA); (vi) gasoline prices, (vii) heating oil prices, and (viii) an index of industrial raw materials. Following the conventional terminology in the real-time macroeconomic forecasting lit- Downloadable! Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and similar real-time variables. Mindful of the importance of Brent crude oil as a global price benchmark, we extend consideration to the North Sea based Real-time forecast combinations for the oil price Journal of Applied Econometrics; The role of uncertainty, sentiment and cross-country interactions in G7 output dynamics Canadian Journal of Economics; Forecasting global recessions in a GVAR model of actual and expected output International Journal of Forecasting Real-time Forecast Combinations for the Oil Price – Discussion Paper no.494 National Institute of Economic and Social Research Real-time Forecast Combinations for the Oil Price Anthony Garratt, Shaun P. Vahey, Yunyi Zhang Abstract Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. Real-time forecast combinations for the oil price. The real-time data set is used in Garratt, A., Vahey, S. P. & Zhang, Y. (2018) `Real-time forecast combinations for the oil price'. We include the replication paper, database documentation and the data set. Please contact Yunyi Zhang (Yunyi.Zhang@warwick.ac.uk) if you have any questions.
10 Oct 2018 National Institute of Economic and Social Research. Real-time Forecast Combinations for the Oil Price. Anthony Garratt, Shaun P. Vahey, Yunyi
Authors: Anthony Garratt¹, Shaun P. Vahey², Yunyi Zhang³ Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. 10 Oct 2018 National Institute of Economic and Social Research. Real-time Forecast Combinations for the Oil Price. Anthony Garratt, Shaun P. Vahey, Yunyi Real-Time Forecasts of the Real Price of Oil Users of real oil price forecasts include governments at the state and Real-Time Analysis of Oil Price Risks using Real-Time Forecast Accuracy of Forecast Combinations at Quarterly Horizons. Keywords. Oil price. Forecasting. Combinations. Real-time data. Brent forecast of the real price of oil and how it can be improved using forecast combinations. We forecast oil price using forecast combination over time-varying parameter models. •. The mean squared predictive error reduction is as high as 17%.
monthly oil futures prices to forecast the nominal price of oil in real time mainly identified by a combination of sign restrictions and bounds on impact price
In this paper, we forecast real prices of crude oil using real-time forecast combinations over time-varying parameter (TVP) models with single predictor. We reveal the significant predictability at all horizons up to 24 months. Forecasting the real price of oil - Time-variation and forecast combination The main focus of this work is to generate real-time forecasts of the real price of oil and to evaluate their out-of-sample performance. All the data used in this work are based on the premise of being subject to real-time data constraints. Forecast combinations have received little attention in the oil price forecasting literature to date. We demonstrate that over the last 20 years suitably constructed real-time forecast combinations would have been systematically more accurate than the no-change forecast at horizons up to 6 quarters or 18 months. Recently, a number of alternative econometric oil price forecasting models has been introduced in the literature and shown to be more accurate than the no-change forecast of the real price of oil. We investigate the merits of constructing real-time forecast combinations of six such models. Forecast combinations are promising for four reasons. Research paper: “Real-time Forecast Combinations for the Oil Price”, joint with Anthony Garratt and Yunyi Zhang. Journal of Applied Econometrics, 2019. Database, documentation, appendices and draft paper on this webpage.
Downloadable! Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their
Downloadable! Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their Authors: Anthony Garratt¹, Shaun P. Vahey², Yunyi Zhang³ Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. 10 Oct 2018 National Institute of Economic and Social Research. Real-time Forecast Combinations for the Oil Price. Anthony Garratt, Shaun P. Vahey, Yunyi Real-Time Forecasts of the Real Price of Oil Users of real oil price forecasts include governments at the state and Real-Time Analysis of Oil Price Risks using Real-Time Forecast Accuracy of Forecast Combinations at Quarterly Horizons. Keywords. Oil price. Forecasting. Combinations. Real-time data. Brent forecast of the real price of oil and how it can be improved using forecast combinations.
The real-time data set is available for download from shaunvahey.com. Keywords : Real oil price forecasting, Brent crude oil, Forecast combina- tion. ∗. We thank
Downloadable! Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their
Downloadable! Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their Authors: Anthony Garratt¹, Shaun P. Vahey², Yunyi Zhang³ Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. 10 Oct 2018 National Institute of Economic and Social Research. Real-time Forecast Combinations for the Oil Price. Anthony Garratt, Shaun P. Vahey, Yunyi Real-Time Forecasts of the Real Price of Oil Users of real oil price forecasts include governments at the state and Real-Time Analysis of Oil Price Risks using Real-Time Forecast Accuracy of Forecast Combinations at Quarterly Horizons. Keywords. Oil price. Forecasting. Combinations. Real-time data. Brent forecast of the real price of oil and how it can be improved using forecast combinations. We forecast oil price using forecast combination over time-varying parameter models. •. The mean squared predictive error reduction is as high as 17%. The price of oil, or the oil price, generally refers to the spot price of a barrel of benchmark crude The authors note that the price of oil has also increased at times due to greater In March 2014, Steve Briese, a commodity analyst, had forecast a decline of world price to $75 from $100, based on 30 years of extra supply.