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A Tug of War: Overnight Versus Intraday Expected Returns

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A Tug of War: Overnight Versus Intraday Expected Returns A Tug of War: Overnight Versus Intraday Expected Returns Dong Lou, Christopher Polk, and Spyros Skouras1 First draft: August 2014 This version: January 2016 1 Lou: Department of Finance, London School of Economics, London WC2A 2AE, UK and CEPR. Email [email protected]. Polk: Department of Finance, London School of Economics, London WC2A 2AE, UK and CEPR. Email [email protected]. Skouras: Athens University of Economics and Business. Email sk- [email protected]. We are grateful to John Campbell, Randy Cohen, Josh Coval, Roger Edelen, Andrea Frazzini, Narasimhan Jegadeesh, Marcin Kacperczyk, Toby Moskowitz, Paul Tetlock, Sheridan Titman, Dimitri Vayanos, Tuomo Vuolteenaho and seminar participants at Duisenberg School of Finance and Tin- bergen Institute, Hong Kong University, Hong Kong University of Science and Technology, IDC Herzliya, IESE Business School, Imperial College, London Business School, London School of Economics, Luxembourg School of Finance, University of Bristol, University of Minho, University of Minnesota, University of South- ern California, University of Zurich, 2015 Adam Smith Asset Pricing Conference, 2015 Crete Conference on Research on Economic Theory and Econometrics, 2014 Financial Research Association conference, 2015 NBER Behavioral Finance Meeting, 2015 NBER Asset Pricing Meeting, 2015 Western Finance Association Annual Meeting, ArrowStreet Capital, and Point72 Asset Management for helpful comments. We thank Andrea Frazzini, Ken French, and Sophia Li for providing data used in the analysis as well as Huaizhi Chen and Michela Verardo for assistance with TAQ. Financial support from the Paul Woolley Centre at the LSE is gratefully acknowledged. A Tug of War: Overnight Versus Intraday Expected Returns Abstract We show that momentum profits accrue entirely overnight while profits on all other trad- ing strategies studied occur entirely intraday. Indeed, for four-factor anomalies, intraday re- turns are particular large as there is a partially-offsetting overnight premium of the opposite sign. Since our findings strongly reject simple neoclassical stories of these patterns, we pro- pose a clientele explanation based on two complimentary tests. We first link cross-sectional and time-series variation in our decomposition of momentum expected returns to variation in institutional momentum trading, generating variation in overnight-minus-intraday mo- mentum return spreads of approximately 2 percent per month. We then document the importance of clienteles more generally, by showing strong overnight and intraday return continuation, as well as cross-period reversal effects, all lasting for years. JEL classification: G12, N22 1 Introduction Understanding cross-sectional variation in average returns is crucial for testing models of market equilibrium. Indeed, over the last two decades, researchers have documented a rich set of characteristics that describe cross-sectional variation in average returns, thus providing a tough test to our standard models of risk and expected return.2 We deliver remarkable new evidence about the cross-section of expected returns through a careful examination of exactly when expected returns accrue. In particular, we decompose the abnormal profits associated with these characteristics into their overnight and intraday components.3 We find that 100% of the abnormal returns on momentum strategies occur overnight; in stark contrast, the average intraday component of momentum profits is eco- nomically and statistically insignificant. This finding is robust to a variety of controls and risk-adjustments, is stronger among large-cap stocks and stocks with relatively high prices, and is true not only for a standard price momentum strategy but also for earnings and industry momentum strategies. In stark contrast, the profits on size and value (and many other strategies, as discussed below) occur entirely intraday; on average, the overnight com- ponents of the profits on these two strategies are economically and statistically insignificant. We further show that our finding continues to hold even in the most recent 10-year subperiod. It is possible that variation in risk drives our findings that momentum profits accrue overnight while size and value premiums instead accrue intraday. However, we find no evidence that standard risk factors explain our results. Recent work has also highlighted the importance of FOMC announcements. 4 Yet, momentum strategies are not profitable around FOMC announcements, with both overnight and intraday components close to zero. As a consequence, we argue that our results present a strong challenge to simple neoclassical explanations of these cross-sectional patterns, particularly momentum. 2 Both risk-based, behavioral, and limits-to-arbitrage explanations of the value and/or momentum effects have been offered in the literature. A partial list includes Barberis, Shleifer, and Vishney (1998); Hong and Stein (1999); Daniel, Hirshleifer, and Subramanyam (2001); Lettau and Wachter (2007); Vayanos and Woolley (2012); and Campbell, Giglio, Polk, and Turley (2014). 3 A more precise explanation of our analysis is that we decompose returns into components based on exchange trading and non-trading periods. However, we refer to these two as intraday and overnight for simplicity’s sake. Though the weekend non-trading period contains two intraday periods, we show in the paper that our results are not particularly different for this non-trading period. We thank Mike Hertzel for suggesting we confirm that the weekend is not special in this regard. 4 See Savor and Wilson (2014), Lucca and Moench (2015), and Cieslak, Morse, and Vissing-Jorgenson (2015). 1 Since the momentum phenomenon is sometimes viewed as underreaction to news, and since a significant amount of firm-specific news is released after markets close, another pos- sibility is that news drives the differences we find. However, we find no statistical difference in our decomposition across news and no-news months, defined as months with and without an earnings announcement or news coverage in Dow Jones Newswire, respectively. Our analysis then studies patterns in the cross-section not captured by the four-factor Fama-French-Carhart model. We show that the premiums for profitability, investment, beta, idiosyncratic volatility, equity issuance, discretionary accruals, and turnover occur intraday. Indeed, by splitting abnormal returns into their intraday and overnight components, we find that the intraday premiums associated with these characteristics are significantly stronger than that from close to close. These results thus imply, which we then confirm, the striking finding that these characteristics have an economically and statistically significant overnight premium that is opposite in sign to their well-known and often-studied total effect. A closer look reveals that in every case a positive risk premium is earned overnight for the side of the trade that might naturally be deemed as riskier. In particular, firms with low return-on-equity, or firms with high investment, market beta, idiosyncratic volatility, equity issuance, discretionary accruals, or share turnover all earn a positive premium overnight.5 We also include the one-month past return in our analysis. Interestingly, we find that the negative premium that previous research has documented from close to close turns out to be realized entirely overnight. Thus, the two past-return based strategies, momentum and short-term reversal, are alike in our overnight/intraday decomposition. We also find that the overnight premium for short-term reversal is more negative than the corresponding close-to-close estimate, and thus there is, on average, a partially offsetting positive premium intraday. We find similar results in our non-US markets sample. Of course, to be persuasive, our decomposition must be reliable and robust. We exclude microcaps (i.e., stock in the bottom size quintile of the NYSE sample) and low-price stocks. When sorting stocks into portfolios, we only examine value-weight strategies and generate breakpoints using only NYSE stocks. We confirm our results using four different measures of open price, including the volume-weighted average price during the first half-hour the market is open as well as the midpoint of the quoted bid-ask spread at the open. The former 5 Merton (1987) argues that both beta and idiosyncratic volatility can have positive premiums in a world where investors cannot fully diversify. Campbell, Polk, and Vuolteenaho (2010) link similar accounting risk measures to cash-flow beta. 2 measure ensures that our open price is tradable while the latter ensures that bid-ask bounce is not responsible for any of our findings. We also show that our findings are robust to examining subsequent prices during the day. As our results are inconsistent with simple neoclassical explanations, we instead consider the possibility that clienteles drive these intraday-overnight differences. To this end, we exploit two different but complimentary ways of identifying potential clienteles. We first study a specific momentum clientele linked to a permanent source of investor heterogeneity, individuals vs. institutions. It’s reasonable to suspect that these two group may have different preferences, not only in terms of whether they buy or sell momentum stocks but also in terms of when they prefer to trade. Therefore, we link institutional activity to our momentum decomposition in three steps. We first examine when institutional investors likely initiate trades. Specifically, we link changes in institutional ownership to
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