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首页> 外文期刊>The North American journal of economics and finance >Time-varying predictability of oil market movements over a century of data: The role of US financial stress
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Time-varying predictability of oil market movements over a century of data: The role of US financial stress

机译：百年数据表明石油市场走势的时空可预测性：美国金融压力的作用

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摘要

In this paper we analyze whether a news-based measure of financial stress index (FSI) in the US can predict West Texas Intermediate oil returns and (realized) volatility over the monthly period of 1889:01 to 2016:12, using a dynamic conditional correlation multivariate generalized auto-regressive conditional heteroscedasticity (DCC-MGARCH) model. Our results show that, standard linear Granger causality test fail to detect any evidence of predictability. However, the linear model is found to be misspecified due to structural breaks and nonlinearity, and hence, the result of no causality from FSI to oil returns and volatility cannot be considered reliable. When we use the DCC-MGARCH model, which is robust to such misspecifications, in 75 percent and 80 percent of the sample periods, FSI in fact do strongly predict the oil returns and volatility respectively. Overall, our results highlight that FSI is helpful in predicting oil returns and volatility, when one accounts for nonlinearity and regime changes through a robust time-varying model.
机译：在本文中，我们使用动态条件分析了基于新闻的美国金融压力指数（FSI）量度是否可以预测1889：01至2016：12月度的西德克萨斯中质原油收益率和（已实现的）波动率相关多元广义自回归条件异方差（DCC-MGARCH）模型。我们的结果表明，标准线性Granger因果关系检验无法检测到任何可预测性的证据。但是，由于结构破裂和非线性，线性模型被错误指定，因此，从FSI到回油和波动率没有因果关系的结果不能被认为是可靠的。当我们使用DCC-MGARCH模型（对这种错误指定具有鲁棒性）时，在75％和80％的采样期间中，FSI实际上确实可以分别强烈预测回油和挥发性。总的来说，当人们通过一个强大的时变模型考虑非线性和状态变化时，FSI有助于预测回油和挥发性。

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