02174cas a2200253 a 4500 AALejournalIMF016424 230101c9999 xx r poo 0 0eng d 5.00 USD 9781513524276 1018-5941 BD-DhAAL BD-DhAAL Beckers, Benjamin. Forecasting the Nominal Brent Oil Price with VARs-One Model Fits All? / Benjamin Beckers, Samya Beidas-Strom. Washington, D.C. : International Monetary Fund, 2015. 1 online resource (32 pages) IMF Working Papers <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required Electronic access restricted to authorized BRAC University faculty, staff and students We carry out an ex post assessment of popular models used to forecast oil prices and propose a host of alternative VAR models based on traditional global macroeconomic and oil market aggregates. While the exact specification of VAR models for nominal oil price prediction is still open to debate, the bias and underprediction in futures and random walk forecasts are larger across all horizons in relation to a large set of VAR specifications. The VAR forecasts generally have the smallest average forecast errors and the highest accuracy, with most specifications outperforming futures and random walk forecasts for horizons up to two years. This calls for caution in reliance on futures or the random walk for forecasting, particularly for near term predictions. Despite the overall strength of VAR models, we highlight some performance instability, with small alterations in specifications, subsamples or lag lengths providing widely different forecasts at times. Combining futures, random walk and VAR models for forecasting have merit for medium term horizons. Mode of access: Internet Beidas-Strom, Samya. IMF Working Papers; Working Paper ; No. 2015/251 Full text available on IMF http://elibrary.imf.org/view/journals/001/2015/251/001.2015.issue-251-en.xml IMF e-Library