Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 507, Issue -, Pages 446-469Publisher
ELSEVIER
DOI: 10.1016/j.physa.2018.05.061
Keywords
Granger causality in quantiles; Quantile regression; Forecast of oil distribution; Forecast evaluation
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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. (C) 2018 Elsevier B.V. All rights reserved.
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