By |Published On: February 12th, 2015|Categories: Research Insights, Momentum Investing Research|

A Tug of War: Overnight Versus Intraday Expected Returns

Abstract:

We decompose the abnormal profi…ts associated with well-known patterns in the cross-section of expected returns into their overnight and intraday components. We show that, on average, all of the abnormal returns on momentum strategies remarkably occur overnight while the abnormal profi…ts on the other trading strategies we consider primarily occur intraday. These patterns are extremely robust across subsamples and indeed are stronger for large-cap and high-price stocks. We argue that investor heterogeneity may explain why momentum pro…fits tend to accrue overnight. We …first provide evidence that, relative to individuals, institutions prefer to trade during the day and against the momentum characteristic. We then highlight conditional patterns that reveal a striking tug of war. Either in the time series, when the amount of momentum activity is particularly low, or in the cross-section, when the typical institution holding a stock has a particularly strong need to rebalance, we …find that momentum returns are even larger overnight and more strongly reverse during the day. Both cases generate variation in the spread between overnight and intraday returns on the order of two percent per month.

Alpha Highlight:

Months ago we highlighted a paper on intraday momentum, which states that the first half-hour return predicts the last half-hour returns. We find no evidence to support this result from our in-house backtests.

  

This paper, taking the opposite view, points out that 100% of the momentum premiums remarkably occur overnight, rather than intraday.

We must be careful in interpreting this papers results because Cooper, Cliff, and Gulen show that ALL returns associated with stocks are from holding overnight risk. This is shown in the figure below (from Cooper, Cliff and Gulen):

98% of the products we hold are exchange-traded products which are guaranteed by AAA rated clearing houses and exchanges Exchange traded products are more liquid, especially in times of volatility when yerou would need the liquidity the most. OTC derivatives have counter-party risk with the firm you are working with (think of Bear Stearns and Lehman). In the 2008 crisis we were the largest US broker that didn’t require or take any help from the US govt. In fact, we were the largest US broker by equity capital for a few days leading up to TARP when the govt stepped in to save our competitors. In the next financial meltdown, what if the US Govt can’t or won’t step in to save JP Morgan or GS? What if these firms become the next Lehman/Bear with their risky OTC product exposure? A big differentiator for IB is our conservative management. Because our founder & CEO has a personal stake of over 80%, we do not take such risks that put our customers and business at risk short term OR long term. These other brokers’ (and banks) decision makers and management do everything they can to maximize shareholder value as their compensation structure depends heavily on their quarterly earnings and stock price. We're a global broker with over $5bn of equity capital. Our brokerage subsidiary holds over 6 times its regulatory requirements. I think JP Morgan is struggling to keep enough equity capital that is being required of them for Basel III (see this article for a very recent example). Our $5bn+ of equity capital is held in a basket of global currencies to diversify our risk in case one region of the world (e.g. US govt fails or defaults and USD blows up) goes down then our equity capital is still hedged. The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

To test whether momentum premiums occur intraday or overnight, this paper decomposes the close-to-close return into 2 components: intraday return and overnight return. In other words, overnight return plus intraday return will equal the close-to-close return. The paper calculates the components of close-to-close return using the methodology below:

2014-12-12 13_17_37-Overnight momentum.pdf - Adobe Reader

intraday return vs. overnight return

The paper examines the holding-period returns of a momentum strategy (MOM). Following the method set forth in Jegadeesh and Titman (1993), the paper measures momentum over a 12-month ranking period and then eliminates the prior month before forming portfolios. In addition to momentum, several other strategies are tested in the remainder of the paper: size, value, earnings momentum, industry momentum, profitability, investment, idiosyncratic volatility, beta, turnover, equity issuance, discretionary accruals, and short-term reversals.

Key Findings:

Panel A lists the close-to-close returns of the momentum strategy. As discussed above, close-to-close return equals the sum of the overnight return and the intraday return. Momentum seems to show up in close-to-close returns. Panel B shows the main result of this paper: Almost ALL of the abnormal returns in the momentum strategy are generated overnight, rather than intraday. Specifically, the overnight 3-factor alpha is a significant 0.95%, while the intraday 3-factor alpha is an insignificant 0.11%.

2014-12-12 16_42_18-2014-12-12 13_35_21-Overnight momentum.pdf - Adobe Reader.png - Windows Photo Vi

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

In contrast, the premiums on Size and Value strategies (and many other strategies listed above) occur entirely intraday (Table IV in this paper).

Potential Explanations:

So what are the possible explanations of overnight momentum premiums? The paper provides three possible explanations:

  1. Traditional models of risk? —- No: Table II shows the Fama and French’s three-factors does not do a good job of accounting for the overnight momentum premiums.
  2. Behavioral explanations? —- No: From a behavioral perspective, investors’ underreaction to news is a potential contributor to MOM premiums. As we know, some news is released before or after markets close, including earnings announcements. So the paper examines whether news releases may explain overnight MOM. –> Results: Table IV shows no statistical evidence to support this hypothesis.
  3. Investor heterogeneity? —- Yes: The paper argues that investor heterogeneity may help explain the overnight momentum premiums. Specifically, the paper tests the degree of institutional activity overnight and intraday. Two questions are when institutional investors tend to trade and what types of stocks they trade.
  • WHEN do institutions trade: The paper hypothesizes that institutional investors tend to trade intraday, and do their trading near the market close. However, individuals are more likely to evaluate their portfolios after work and thus they tend to execute trades when markets open. –> Results: institutions tend to trade intraday while individuals are more likely to trade overnight.
  • WHAT types of stocks do institutions trade. –> Results: Table VI illustrates that institutions prefer to trade against the momentum characteristic during the day.

In sum, virtually all of the abnormal returns associated with momentum strategies occur overnight, and one reason for this appears to be investor heterogeneity, as institutions trade more heavily at the close and against momentum during the day, while individuals trade at the open, and presumably trade momentum stocks.

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
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.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

Join thousands of other readers and subscribe to our blog.