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Causality in quantiles and dynamic relations in energy markets: (De)tails matter

机译：能源市场中分位数的因果关系和动态关系：（重要）细节

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摘要

In this article we investigate the dynamic relations between crude oil price returns and a set of energy price returns, namely diesel, gasoline, heating, and the natural gas. This is performed by means of Granger non-causality tests for US closing spot prices over the period from January 1997 to December 2017. In previous studies this has been done by testing for the added predictive value of including lagged returns of one energy price in predicting the conditional expectation of another. In this paper we instead focus on different ranges of the full conditional distribution, and thus market states, within the framework of a dynamic quantile regression model, and identify the quantile ranges from which causality arises. The results constitute a richer set of findings than what is possible by just considering a single moment of the conditional distribution, which can be useful for implementing better substitution investment strategies and effective policy interventions. We find several interesting uni-directional dynamic relations between the employed energy price returns, especially in the tail quantiles, but also bi-directional causal relations between energy price returns for which the classical Granger non-causality test suggests otherwise. Our results are robust to alternative measures of the price of oil and different data frequencies.
机译：在本文中，我们研究了原油价格回报与一组能源价格回报（即柴油，汽油，供暖和天然气）之间的动态关系。这是通过对1997年1月至2017年12月期间美国收盘现货价格的格兰杰非因果检验来完成的。在以前的研究中，这是通过检验包括在预测中包括一个能源价格的滞后收益在内的附加预测价值来完成的。对另一个人的有条件期望。在本文中，我们将重点放在动态分位数回归模型框架内的完整条件分布的不同范围，从而关注市场状态，并确定因果关系产生的分位数范围。与仅考虑条件分布的单个时刻相比，结果构成了更丰富的发现，这对于实施更好的替代投资策略和有效的政策干预非常有用。我们发现，在使用的能源价格收益率之间，尤其是在尾部分位数之间，存在一些有趣的单向动态关系，但在能源价格收益率之间也存在双向因果关系，而经典的Granger非因果关系检验表明这种关系。我们的结果对于替代油价和不同数据频率的度量是可靠的。

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