Oil Tail Risks and the Forecastability of the Realized Variance of Oil-Price: Evidence from Over 150 Years of Data
Afees Salisu,
Christian Pierdzioch and
Rangan Gupta
No 202146, Working Papers from University of Pretoria, Department of Economics
Abstract:
We examine the predictive value of tail risks of oil returns for the realized variance of oil returns using monthly data for the modern oil industry (1859:10-2020:10). The Conditional Autoregressive Value at Risk (CAViaR) framework is employed to generate the tail risks for both 1% and 5% VaRs across four variants of the CAViaR framework. We find evidence of both in-sample and out-of-sample predictability emanating from both 1% and 5% tail risks. Given the importance of real-time oil-price volatility forecasts, our results have important implications for investors and policymakers.
Keywords: Oil Tail Risks; Realized Variance of Oil-Price; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 Q02 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2021-06
New Economics Papers: this item is included in nep-cwa, nep-ene, nep-ore and nep-rmg
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Journal Article: Oil tail risks and the forecastability of the realized variance of oil-price: Evidence from over 150 years of data (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202146
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