Ebook Market Frictions, Price Delay, and the Cross-Section of Expected Returns
Predictability in the cross-section of returns has fueled much of the market efficiency debate. Whether such predictability is due to mismeasurement of risk or constitutes an efficient market “anomaly” remains unresolved, due in large part to the joint hypothesis problem. Complicating this debate, however, is the fact that traditional asset pricing theory assumes markets are friction less and complete and investors are well-diversified, yet ample empirical evidence demonstrates the existence of sizeable market frictions and large groups of poorly diversified investors. We argue and show that accounting for these features of the market critically aids our understanding of the cross section of returns.
Rather than focus on a particular friction in the market, or a particular set of poorly diversified investors, we examine the characteristics of firms most likely to suffer from frictions in the economy and/or have concentrated investor bases. Specifically, we characterize how affected a firm is from market frictions by the level of “delay” in its share price. Firms whose stock prices respond sluggishly to market information are those most likely facing the most severe frictions.
The link between the speed of information diffusion and market frictions is consistent with many theories that incorporate a variety of frictions and investor constraints. For instance, theories of incomplete markets and limited stock market participation (e.g., Merton (1987), Hirshleifer (1988), Basak and Cuoco (1998), Shapiro (2002)) generate a lack of risk sharing that results in segmented markets and return premia related (inversely) to the breadth of ownership and (positively) to idiosyncratic risk.
These models are also consistent with the notion of a “neglected” stock premium (e.g., Arbel and Strebel (1982), Arbel, Carvell, and Strebel (1983), Arbel (1985)). Although some of these models do not provide an explicit role for the speed of information diffusion, they argue that institutional forces and transactions costs will delay the process of information incorporation, particularly for less visible and more segmented firms. Other related models are those of Hong and Stein (1999), who develop a model of gradual information diffusion and Peng (2002), who shows that information capacity constraints cause a delay in the response of asset prices to fundamental and firm-specific shocks. In these models, the speed of information diffusion is related to expected returns.
In addition, models of asymmetric information (the depth as opposed to the breadth of information, e.g., Jones and Slezak (1999), Easley and O’Hara (2000), Easley, Hvidkjaer, and O’Hara (2002)) and models of investor sentiment (e.g., DeLong, Shleifer, Summers, and Waldmann (1992), Shleifer and Vishny (1997)) may generate slow price responses in firms that face higher risk of informed trading or noise trading, respectively. These effects will be more acute in small, less visible firms. Finally, stocks may experience slow price movement simply because the market for their shares is illiquid. Illiquidity may arise from many sources, including those above. Hence, many frictions may play a role in causing delay.
We employ the level of price delay as a summary measure for how severely these potential frictions impact the price process of a stock. Our primary goal is to quantify the impact of price delay on asset prices without regard to the source of delay or market friction that causes it. Once the importance of delay is established, a secondary goal is to begin to distinguish which frictions matter most and which theories are most consistent with the data. For instance, we will show that our results stem from more than just a liquidity effect. Furthermore, stock visibility and firm neglect seem to be more consistent with the data than theories of asymmetric information or sentiment risk.
We find that small, volatile, less visible, and neglected firms exhibit significant price delay. Delayed firms exhibit a large return premium in the cross-section, even after accounting for known return premia associated with the market, firm size, book-to-market equity (BE/ME), and momentum, as well as microstructure and liquidity effects. Firms in the highest decile of delayed response generate abnormal average returns 92 basis points higher per month than firms in the lowest delay decile (quickest response). These results are robust to a number of specifications and subsamples. Moreover, this spread in returns derives solely from the highest delay decile.
This appears consistent with many frictional theories which posit that only the most constrained or inefficient assets carry a premium, but unconstrained assets do not underperform. As an additional check on the usefulness of our delay measure, we also examine the price response of firms’ equity to two specific news events: earnings announcements and extreme (top and bottom 5 percent) movements in the market index return. We find that post announcement drift (to both events) is present only for the most delayed firms.
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