Forecasting the Price of Oil

By Ron Alquist, Lutz Kilian, Robert J. Vigfusson. 2010

486 citations recorded by the source corpus.

We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications? Are real or nominal oil prices predictable based on macroeconomic aggregates? Does this predictability translate into gains in out-of-sample forecast accuracy compared with conventional no-change forecasts? How useful are oil futures markets in forecasting the price of oil? How useful are survey forecasts? How does one evaluate the sensitivity of a baseline oil price forecast to alternative assumptions about future demand and supply conditions? How does one quantify risks associated with oil price forecasts? Can joint forecasts of the price of oil and of U.S. real GDP growth be improved upon by allowing for asymmetries?

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Citations in the corpus

What Central Bankers Need to Know about Forecasting Oil Prices (2014, background): “As in the literature on forecasting asset prices, the traditional benchmark in forecasting the real price of oil has been the random walk forecast or no-change forecast (see, e.g., Alquist et al., 2013).”
NONLINEARITIES IN THE OIL PRICE–OUTPUT RELATIONSHIP (2010, unknown): “Further analysis in Alquist et al. (2010) shows that nonlinear models tend to produce systematically less accurate forecasts than the AR(4) benchmark model for real GDP growth through most of the evaluation period.”
Forecasting oil price realized volatility using information channels from other asset classes (2017, background): “See, for example, Abramson and Finizza (1991), Huntington (1994), Alquist et al. (2013), Baumeister and Kilian (2102, 2014, 2015). for instance, Hansen and Lunde, 2005; Engle and Sun, 2007; Tay et al., 2009).”
Forecasting: theory and practice (2020, background): “However, the crude oil price movement suffers from complex features such as nonlinearity, irregularities, dynamics and high volatility (Kang et al., 2009; Alquist et al., 2013; Herrera et al., 2018),”
Commodity-price comovement and global economic activity (2020, unknown): “See section 3.3 for details.”
Oil Price Shocks: Causes and Consequences (2014, background): “Rather the relevant volatility measure is the volatility of the real price of oil at horizons relevant to durables purchase and investment decisions, which is much more stable and typically measured in years or even decades rather than months (e.g., Kilian and Vigfusson 2011b, Alquist et al. 2013).”
Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons (2015, background): “(2010), Alquist et al. (2012), and Ferraro, Rogoff and Rossi (2012).”
Understanding the Decline in the Price of Oil since June 2014 (2015, unknown): “Indeed, there is no evidence of a systematic predictive relationship between the trade-weighted U.S. exchange rate and the price of oil over extended periods of time (see Alquist et al. 2013).”
Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach (2015, unknown): “Its forecast accuracy has been examined extensively in the literature (see, e.g., Alquist, Kilian, and Vigfusson 2013; Baumeister and Kilian 2012, 2014a).”
Do Consumers Recognize the Value of Fuel Economy? Evidence from Used Car Prices and Gasoline Price Fluctuations (2016, unknown): “It is also the case that a no change forecast for oil prices preforms as well, or better than, alternative forecasts based on futures markets or expert surveys (Alquist and Kilian 2010; Alquist, Kilian, and Vigfusson 2013).”