Hayong Yun, associate professor of finance at the Eli Broad College of Business at Michigan State University, has long had an interest in electricity and its impact on business.
In fact, his recent research shows the impact electricity has on predicting the stock market. The engineer-turned-finance-professor recently completed research with colleagues at two other major universities that shows that electricity usage is a beneficial predictor of the stock market.
“Tracking simple electricity usage is helpful as a directive in discerning market movements,” said Yun, who was joined in the research by Zhi Da at the University of Notre Dame, and Dayong Huang at the University of North Carolina.
The team looked at data from 1956-2010 in the U.S., Japan, and the UK, and found that over that time, each 1 percent increase in electricity usage corresponded to a 0.92 percent decline across the board in stock market measures, Yun explained.
The concept, known as “countercyclical risk premium,” shows how the market and business cycle under normal conditions move in different directions.
“Simple year-over-year industrial electricity usage growth rate has strong and significant predictive power for future stock market excess returns in horizons ranging from one month up to one year,” the research team wrote.
The study looks at all factors throughout the time period—whether it was extreme, such as a recession or inflation—but not focused on those issues only. And the results indicated that for the entire period as electric use increases, it logically follows that industrial production goes up. And the countercyclical effect would be that the stock market would perform modestly. In general terms that means that low industrial electricity usage today will be followed by high excess stock returns tomorrow.
“This is high quality data,” Yun said.
The data is accurately measured over the years studied, and it is high quality data that has historically been effective in determining market action. The study connects macroeconomic quantities with future stock market performances, Yun said. Other academic literature using price-based financial variables often predict future stock market performance better than quantity-based macroeconomic indicators, such as GDP, despite instinctive thought that macroeconomic quantity based variables should well predict future stock market performances.
Yun said it has only been recently that researchers have been making progress in using macroeconomic indicators to predict future stock market performance, and that this research went further using high data quality of industrial electricity consumption is crucial to improving our understanding of the relationship between macroeconomic activity and future stock market performance.
Some of Yun’s earlier research looked at residential electricity and asset prices to explain household consumptions and expected returns of assets.