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

被引:38
作者
Bonaccolto, G. [1 ]
Caporin, M. [2 ]
Gupta, R. [3 ]
机构
[1] Univ Enna Kore, Viale Olimpiadi, I-94100 Enna, Italy
[2] Univ Padua, Dept Stat Sci, Via C Battisti 241, I-35121 Padua, Italy
[3] Univ Pretoria, Dept Econ, ZA-0002 Pretoria, South Africa
关键词
Granger causality in quantiles; Quantile regression; Forecast of oil distribution; Forecast evaluation; ECONOMIC-POLICY UNCERTAINTY; CONSISTENT NONPARAMETRIC TEST; DENSITY FORECASTS; TIME-SERIES; GRANGER CAUSALITY; PRICE; VOLATILITY; QUANTILE; US; PROBABILITY;
D O I
10.1016/j.physa.2018.05.061
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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.
引用
收藏
页码:446 / 469
页数:24
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