Momentum in firm fundamentals, i.e., earnings momentum, explains the performance of strategies based on price momentum. Earnings surprise measures subsume past performance in cross sectional regressions of returns on firm characteristics, and the time-series performance of price momentum strategies is fully explained by their covariances with earnings momentum strategies. Controlling for earnings surprises when constructing price momentum strategies significantly reduces their performance, without reducing their high volatilities. Controlling for past performance when constructing earnings momentum strategies reduces their volatilities, and eliminates the crashes strongly associated with momentum of all types, without reducing the strategies’ high average returns. While past performance does not have independent power predicting the cross section of expected returns, it does predicts stock comovements, and is thus important for explain cross sectional variation in realized returns
We find strong evidence linking the momentum pattern in equity returns with a prominent measure of macroeconomic conditions, specifically the funding environment. We show that the size and consistency of the momentum premium varies systematically across funding states. Furthermore, we find evidence that the relationship between momentum returns and firm characteristics (documented in previous research) is conditional on the funding environment. After controlling for the funding state, we find that the importance of market states and return dispersion disappears. Additionally, funding conditions appear to contain incremental information about the momentum premium even after adjusting for the influence of market states and return dispersion. Overall our results are consistent with the conjecture that transitions in the funding environment encourage investors to revise their portfolio allocations; this reallocation produces inter-temporal variation in the momentum return pattern.
We provide supporting evidence for the momentum life cycle hypothesis proposed by Lee and Swaminathan (2000) around the world. The early-stage strategy that longs low-turnover winner stocks and shorts high-turnover loser stocks significantly outperform both the late-stage strategy that longs high-turnover winners and shorts low-turnover losers and the conventional strategy in most countries. The results are robust and the economic magnitudes are large. The early-stage strategy even delivers positive momentum profits beyond the one-year horizon. Cross-country analysis shows that momentum profits are positively associated with individualism for the late-stage and conventional strategies but not for the early-stage strategy. In contrast, the association between momentum profits and limits-to-arbitrage is positive for the early-stage but negative for the late-stage strategy. Our results appear to support the behavioral momentum model of Daniel, Hirshleifer, and Subrahmanyam (1998) and the arbitrageurs’ mispricing amplifying role of Stein (2009).
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016).
Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.
Performance figures contained herein are hypothetical, unaudited and prepared by Alpha Architect, LLC; hypothetical results are intended for illustrative purposes only. Past performance is not indicative of future results, which may vary. There is a risk of substantial loss associated with trading stocks, commodities, futures, options and other financial instruments. Full disclosures here.