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The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

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

Empirical Economics, 2017, vol. 53, issue 3, No 1, 879-889

Abstract: Abstract A recent strand in the literature emphasizes the role of news-based economic policy uncertainty (EPU) and equity market uncertainty (EMU) as drivers of oil price movements. Against this backdrop, this paper uses a kth-order nonparametric quantile causality test, to analyse whether EPU and EMU predict stock returns and volatility. Based on daily data covering the period of 2 January 1986 to 8 December 2014, we find that, for oil returns, EPU and EMU have strong predictive power over the entire distribution barring regions around the median, but for volatility, the predictability virtually covers the entire distribution, with some exceptions in the tails. In other words, predictability based on measures of uncertainty is asymmetric over the distribution of oil returns and its volatility.

Keywords: Uncertainty; Oil markets; Volatility; Quantile causality (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 Q41 (search for similar items in EconPapers)
Date: 2017
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Working Paper: THE ROLE OF NEWS-BASED UNCERTAINTY INDICES IN PREDICTING OIL MARKETS: A HYBRID NONPARAMETRIC QUANTILE CAUSALITY METHOD (2015) 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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DOI: 10.1007/s00181-016-1150-0

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