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THE ROLE OF NEWS-BASED UNCERTAINTY INDICES IN PREDICTING OIL MARKETS: A HYBRID NONPARAMETRIC QUANTILE CAUSALITY METHOD

Mehmet Balcilar (), Rangan Gupta () and Stelios Bekiros

No 15-02, Working Papers from Eastern Mediterranean University, Department of Economics

Abstract: We emphasize the role of news-based economic policy and equity market uncertainty indices as robust drivers of oil price fluctuations. In that, we utilize a new hybrid nonparametric quantile causality methodology in order to investigate whether EPU and EMU uncertainty measures incorporate critical predictability for oil market returns and volatility. Based on an updated daily database spanning January 1986 to December 2014, we find that both measures present strong predictability over the entire distribution of oil around the median, yet more importantly for volatility forecastability covers the entire distribution except minor divergences in the tails. Therefore, an inherent heterogeneity is observed and an asymmetric pattern over the distribution of oil returns and its volatility exists with respect to uncertainty predictability.

Keywords: Uncertainty; Oil markets; Volatility; Quantile causality (search for similar items in EconPapers)
JEL-codes: C32 C53 Q41 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2015
New Economics Papers: this item is included in nep-ene
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http://repec.economics.emu.edu.tr/RePEc/emu/wpaper/15-02.pdf First version, 2015 (application/pdf)

Related works:
Journal Article: The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method (2017) Downloads
Working Paper: The Role of News-Based Uncertainty Indices in Predicting Oil Markets: A Hybrid Nonparametric Quantile Causality Method (2015)
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