Attention Allocation and Return Co-Movement: Evidence from Repeated Natural Experiments

Abstract

We study how attention allocation affects the composition of market/industry and firm-specific information in stock prices via repeated natural experiments. Using large jackpots of Taiwanese nationwide lotteries as exogenous shocks to investors' attention, we find: (1) individual stock returns co-move more with the market/industry returns on large jackpot days; (2) large jackpots have stronger effects on stock returns' co-movement with the market than with the industry; (3) the effect of large jackpots on return co-movement is stronger for stocks preferred by retail investors; and (4) the market under-reacts to firms' earnings surprises on large jackpot days and reverts within one week. Our findings are consistent with the existing theory that attentionconstrained investors focus more on market-and sector-level information than on firm-specific information. * We appreciate the helpful comments from Yifei Mao, Yu Yuan, Dexin Zhou, Shaojun Zhang, and seminar participants at University of Hong Kong. Tse-Chun Lin gratefully acknowledges research support from the Faculty of Business and Economics at the University of Hong Kong and the Research Grants Council of the Hong Kong SAR government. All errors remain the responsibility of the authors.

Social media, financial reporting opacity, and return comovement: Evidence from Seeking Alpha

“…Our two-period model closely follows the model proposed by Huang et al, (2018) based on the theoretical framework of Kacperczyk et al, (2016). We provide insights on how social media coverage and financial reporting opacity relate to the attention allocation of attention of investors, which further influence the co-movement between firm specific returns and the industry and market returns.…”

“…At time 1, the investor can learn about the shocks m , i e and , ij f by allocating her attention, which is constrained by some positive constant K , known as the learning capacity. We propose to specify the learning process of the investor as follows: our model reduces to the model in Huang et al, (2018).…”

“…After some calculation, we obtain: are constants that can be interpreted as overall measures of information processing cost for all stocks. Since we are not interested in the scenario when there is a scarcity of the attention resources, we assume that K is sufficiently large, so that we always have 0 me   , which is a result documented in Huang et al, (2018).…”

“…In contrast, if the market factor drives the price fluctuation to a greater extent, it is reasonable that asset returns will co-integrate with the market factor, generating higher return co-movement. Our two-period model, which is adapted from the model proposed by Huang et al, (2018), provides insights into how social media coverage and financial reporting opacity relate to the attention allocation of investors, which consequently influence the return co-movement. In this section, we briefly outline the key intuitions and conclusions of our model for conciseness, and refer the readers to Appendix 1 for a complete exposition of the model.…”

“…Our contribution to the original model of Huang et al (2018) is that we consider explicitly the information processing cost in the model. In our model, the information processing cost is directly associated with the attention allocated to the firm-specific shock.…”