The Predictive Power of Industrial Electricity Usage Revisited: Evidence from Non‐Parametric Causality Tests

M. Bonato, Rıza Demirer, Rangan Gupta
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引用次数: 2

Abstract

Da et al. (2015b) report that the industrial electricity usage growth rate carries predictive ability over stock returns up to one year. Using the recently developed nonparametric causality test by Nishiyama et al. (2011), we show that the predictive power of industrial electricity usage can be explained by an “industry effect” that is transmitted via the volatility channel. We argue that the countercyclical premium associated with industrial electricity usage growth is driven by the industry components that drive stock reversals, thus resulting in the negative relationship between today’s industrial electricity usage and stock returns in the future. The findings are in line with the notion that the returns on industry portfolios are informative about macroeconomic fundamentals and suggest that the informational value of industrial electricity usage as a business cycle variable may be an artifact of return reversals driven by past industry performance
重新审视工业用电量的预测能力:来自非参数因果检验的证据
Da等人(2015b)报告称,工业用电量增长率对股票回报率具有长达一年的预测能力。使用Nishiyama等人(2011)最近开发的非参数因果检验,我们表明工业用电量的预测能力可以通过通过波动渠道传播的“行业效应”来解释。我们认为,与工业用电量增长相关的逆周期溢价是由驱动股票反转的行业成分驱动的,因此导致今天的工业用电量与未来的股票回报之间存在负相关关系。研究结果与行业投资组合的回报是关于宏观经济基本面的信息这一概念一致,并表明工业用电量作为一个商业周期变量的信息价值可能是由过去行业表现驱动的回报逆转的产物
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