The Predictive Power of Industrial Electricity Usage Revisited: Evidence from Nonparametric Causality Tests

Matteo Bonato, Riza Demirer and Rangan Gupta

No 201679, Working Papers from University of Pretoria, Department of Economics

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

Keywords: Asset Returns; Industry; Realized Volatility; Nonlinear Causality (search for similar items in EconPapers)
JEL-codes: C22 G1 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2016-11
New Economics Papers: this item is included in nep-ene
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201679

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