Analyzing the economic sources of oil price volatility: An out-of-sample perspective. (15th June 2019)

• Record Type: Journal Article
• Authors: Meng, Fanyi; Liu, Li
• Is Part Of: Energy. Volume 177(2019)
• Page Start: 476
• Page End: 486
• Publication Date: 2019-06-15
• Subjects: Crude oil -- Realized volatility -- Predictive regression -- Forecast combination; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.04.161
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The determinants of oil price changes have been extensively investigated in the literature. However, the economic source of its volatility receives much less attention in existing studies. In this paper, we investigate the predictive ability of macroeconomic variables to oil spot price volatility. Using a variety of predictive regressions, we find that some variables such as lagged oil production uncertainty and futures price volatility have significant effects on current oil volatility in-sample. However, adding any predictor to the autoregressive model cannot consistently improve the predictive ability from the out-of-sample perspective. We find the strong and significant predictability using forecast combinations. The revealed predictability is further demonstrated to be robust to the change of lag order and an alternative evaluation criterion of success ratio. Combination methods can provide more accurate density forecasts of realized volatility than the benchmark model. Highlights: We analyze the predictive ability of economic variables to oil price volatility. Some variables indeed have significant effects on oil volatility in-sample. None of the single variables successfully predicts oil volatility out of sample. We find the strong and significant predictability using forecast combinations. Combination methods can also reveal the predictability of volatility density.