The predictive power of industrial electricity usage revisited: evidence from non‐parametric causality tests

Abstract

Recent research shows that the industrial electricity usage growth rate carries predictive ability over stock market returns up to 1 year. Using the recently developed non‐parametric causality tests 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 market 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 artefact of return reversals driven by past industry performance.

Bitcoin mining activity and volatility dynamics in the power market

“…From an investment planning perspective, price uncertainty and extreme volatility in the electricity market is not only a major operating risk for utility companies, but also crucial for the real economy as electricity price forecasts have become a fundamental input for corporate decisions (Bunn (2004); Eydeland and Wolyniec (2002)). In fact, recent studies show that industrial electricity usage growth rate carries predictive ability over stock returns up to one year (Da et al (2017))) where the predictive power of industrial electricity usage is explained by an "industry effect" that is transmitted via the volatility channel (Bonato et al (2018)). Not surprisingly, there is a growing literature on the predictability of daily electricity prices with a particular focus on the price behavior in the day-ahead spot market.…”