Glued to the TV: Distracted Noise Traders and Stock Market Liquidity

Abstract

In this paper, we study the impact of noise traders’ limited attention on financial markets. Specifically, we exploit episodes of sensational news (exogenous to the market) that distract noise traders. We find that on “distraction days,” trading activity, liquidity, and volatility decrease, and prices reverse less among stocks owned predominantly by noise traders. These outcomes contrast sharply with those due to the inattention of informed speculators and market makers, and are consistent with noise traders mitigating adverse selection risk. We discuss the evolution of these outcomes over time and the role of technological changes.

Paying Attention

“…As a stock's mean weekly number of long trades is 0.0082 (not tabulated), the magnitude of the treatment coefficient is 102% of this mean and, thus, economically important. This result is consistent with previous findings in the literature (Seasholes and Wu, 2007;Barber and Odean, 2008;Lou, 2014;Peress and Schmidt, 2018).…”

“…Table 3 and Column (2) of Table 4 imply that, whereas attention has a strong effect on the decision whether to trade, it has no impact on the decision how much to trade. These results are consistent with the findings in Peress and Schmidt (2018). They are supportive of models assuming a fixed attention cost for stock market participation Subrahmanyam, 1977, 1980;Merton, 1987;Abel et al, 2007;Chien et al, 2012), but difficult to reconcile with models in which investors gradually increase trading with attention (Peng and Xiong, 2006;Van Nieuwerburgh and Veldkamp, 2010).…”

“…8 Also, by considering a rather short time period after the push message, we minimize the likelihood that additional news occurred which trigger the trading of investors. Second, measuring trading patterns over one attention day is standard in the literature (Barber and Odean, 2008;Peress and Schmidt, 2018).…”

“…First, Odean (1999) suggests that investors manage the problem of selecting a few among a large universe of stocks by limiting their choice to those stocks that have caught their attention. Several studies build on this insight and conclude that aggregate attention has an important bearing on stock returns, aggregate trading patterns, and bid-ask spreads (Chen et al, 2005;Seasholes and Wu, 2007;Barber and Odean, 2008;Lehavy and Sloan, 2008;Fang and Peress, 2009;Da et al, 2011;Lou, 2014;Lawrence et al, 2018;Peress and Schmidt, 2018).…”

“…They show that greater attention leads to higher stock prices, larger return volatility, and a delayed return reversal (e.g., Lehavy and Sloan, 2008;Fang and Peress, 2009;Da et al, 2011;Andrei and Hasler, 2014). Peress and Schmidt (2018) develop a model to link retail investor attention to stock return patterns. They empirically confirm the model's prediction that higher retail attention is associated with larger trading volume, liquidity, volatility, and price reversals among stocks owned predominantly by individual investors.…”