Have you ever wondered when you should invest or make a trade in your stock?
By using United States equity market-level data from 1926 through 2015, Oklahoma State University assistant professor of finance Greg Eaton nailed down the predictive power of trading costs in his latest research, “Micro(structure) before Macro? The Predictive Power of Aggregate Illiquidity for Stock Returns and Economic Activity,” which was accepted into the prestigious Journal of Financial Economics. Eaton cut out the volatility component from trading cost measures and found that embedded volatility was causing misleading results.
“One important aspect of our study is how we measure trading cost,” Eaton said. “We document that most measures of trading cost mechanically embed a volatility component, and it’s important to extract that component so we make sure that our results are driven by actual trading costs as opposed to volatility in disguise. Making this adjustment does have an important impact on our results. What we find is that the trading costs before we made the adjustment did not forecast stock returns, but once we extracted the embedded volatility component, we found strong evidence that trading costs do forecast future stock returns.”
By using market-level trading costs measures constructed at a monthly frequency, Eaton was able to forecast stock returns a month in advance. These findings are of particular interest to the investment community and policy makers, but adding to the current literature also sets the stage for future research.
“Our research gives us a better understanding of how asset prices are formed,” Eaton said. “The implication of our research is now we know a little more about how asset prices are formed, specifically how the cost of trading affects an asset’s price and an asset’s future return. An extension of our work could look at the stock level or asset-specific level and examine how cross-sectional variation in trading costs affects asset prices.”
Gregory Eaton is an assistant professor in the finance department at Oklahoma State University. He received his Ph.D. in finance from the University of Georgia in 2016 and a B.S. degree in finance from the University of Missouri in 2007. His research has been published in top peer reviewed journals, including Journal of Financial Economics and Journal of Financial and Quantitative Analysis.