The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk

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dc.contributor.author Bonaccolto, Giovanni
dc.contributor.author Caporin, Massimiliano
dc.contributor.author Gupta, Rangan
dc.date.accessioned 2018-07-26T10:56:21Z
dc.date.issued 2018-10
dc.description.abstract The aim of this study is to analyze the relevance of recently developed news-based measures of economic policy and equity market uncertainty in causing and predicting the conditional quantiles of crude oil returns and risk. For this purpose, we studied both the causality relationships in quantiles through a non-parametric testing method and, building on a collection of quantiles forecasts, we estimated the conditional density of oil returns and volatility, the out-of-sample performance of which was evaluated by using suitable tests. A dynamic analysis shows that the uncertainty indexes are not always relevant in causing and forecasting oil movements. Nevertheless, the informative content of the uncertainty indexes turns out to be relevant during periods of market distress, when the role of oil risk is the predominant interest, with heterogeneous effects over the different quantiles levels. en_ZA
dc.description.department Economics en_ZA
dc.description.embargo 2019-10-01
dc.description.librarian hj2018 en_ZA
dc.description.uri http://www.elsevier.com/locate/physa en_ZA
dc.identifier.citation Bonaccolto, G., Caporin, M. & Gupta, R. 2018, 'The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk', Physica A : Statistical Mechanics and its Applications, vol. 507, pp. 446-469. en_ZA
dc.identifier.issn 0378-4371 (print)
dc.identifier.issn 1873-2119 (online)
dc.identifier.other 10.1016/j.physa.2018.05.061
dc.identifier.uri http://hdl.handle.net/2263/65998
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2018 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Physica A: Statistical Mechanics and its Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Physica A: Statistical Mechanics and its Applications, vol. 507, pp. 446-469, 2018. doi : 10.1016/j.physa.2018.05.061. en_ZA
dc.subject Granger causality in quantiles en_ZA
dc.subject Quantile regression en_ZA
dc.subject Forecast of oil distribution en_ZA
dc.subject Forecast evaluation en_ZA
dc.subject Economic policy uncertainty (EPU) en_ZA
dc.subject Equity market uncertainty (EMU) en_ZA
dc.subject Consistent nonparametric test en_ZA
dc.subject Time series regression en_ZA
dc.subject Causality-in-quantiles test en_ZA
dc.subject Density forecasts en_ZA
dc.subject Generalized autoregressive conditional heteroskedasticity (GARCH) en_ZA
dc.subject Unit root en_ZA
dc.subject Volatility en_ZA
dc.subject Price en_ZA
dc.title The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk en_ZA
dc.type Postprint Article en_ZA


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