Oil volatility risk and stock market volatility predictability: Evidence from G7 countries
Jiabao Feng,
Yudong Wang and
Libo Yin ()
Energy Economics, 2017, vol. 68, issue C, 240-254
Abstract:
Academic research relies extensively on stock market information to forecast oil volatility, with relatively little attention paid to the reverse evidence. Our paper fills this gap by investigating the predictive ability of oil volatility risk to forecast stock market volatility. Using oil volatility risk premium (oil VRP) as the predictor, we find that oil VRP does exhibit statistically and economically significant in-sample and out-of-sample forecasting power for G7 countries, even controlling for some popular macroeconomic variables. These findings are robust when using alternative proxies for volatilities of stock and oil. Furthermore, the strength of the predictive evidence is substantial during relatively high and low level of stock market, while is substantially higher for recessions vis-á-vis expansions. Oil VRP can also contains additional information for predicting a series of macroeconomic variables, which serves as an available explanation for its forecasting ability.
Keywords: Stock realized volatility; Oil volatility risk premium; Predictive regression; Out-of-sample forecast; Economic significance (search for similar items in EconPapers)
JEL-codes: G12 G15 G17 Q02 Q43 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (35)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:68:y:2017:i:c:p:240-254
DOI: 10.1016/j.eneco.2017.09.023
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