Information acquisition and expected returns: Evidence from EDGAR search traffic

Li, Frank Weikai; Sun, Chengzhu

doi:10.1016/j.jedc.2022.104384

Cited by 9 publications

(5 citation statements)

References 64 publications

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“…Before that, empiricists mainly observed the aggregate interest of investors via equilibrium outcomes such as trading volume and returns. Since then a vivid literature has emerged, using different and novel sources of information to measure the attention of market participants more directly (Cao et al, 2021;Lee et al, 2015;Li et al, 2019;Li and Sun, 2022;Rubin and Rubin, 2010;Sicherman, 2016). The empirical analysis in this dissertation further confirms the usefulness of such data sources to track and quantify the attention allocation of financial agents.…”

Section: Main Findingssupporting

confidence: 57%

“…Other and more recent studies construct novel measures that can more directly capture investor attention, such as Google search data (Da et al, 2011), Bloomberg terminal usage (Ben-Rephael et al, 2017), online investment account logins (Sicherman, 2016), the posting volume on the Yahoo! Finance message board (Antweiler and Frank, 2004), the frequency with which a firm's Wikipedia article is edited (Rubin and Rubin, 2010) and search-traffic on the Security Exchange Commission's EDGAR system (Cao et al, 2021;Lee et al, 2015;Li et al, 2019;Li and Sun, 2022). The advantage of these more direct proxies of attention is that they measure revealed attention: if someone is searching on Google or logging in on his investment account, this person is undoubtedly paying attention.…”

Section: Limited Attentionmentioning

confidence: 99%

“…The literature has proposed different proxies for investor attention, such as extreme returns and abnormal trading volume (Barber and Odean, 2008;Gervais et al, 2001), news content (Barber and Odean, 2008), Google search data (Da et al, 2011), posting volume on the Yahoo! Finance message board (Antweiler and Frank, 2004), the frequency with which a firm's Wikipedia article is edited (Rubin and Rubin, 2010), online investment account logins (Sicherman, 2016) and search-traffic on the Security Exchange Commission's Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system (Cao et al, 2021;Lee et al, 2015;Li et al, 2019;Li and Sun, 2022). In this chapter, we measure investor attention during the coronavirus pandemic for news and information about the development of the virus and the resulting economic crisis.…”

Section: Measuring Pandemic Attentionmentioning

confidence: 99%

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Limited Attention, Uncertainty, and Asset Price Dynamics

Verhoeks

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Standard neoclassical models in finance assume that individuals form expectations and make decisions using all available information. While these theories dictate that new information is instantaneously incorporated into asset prices, our minds and cognitive resources are finite and we allocate our attention selectively. Moreover, the amount of information relevant to the valuation of an asset is far from trivial in the current information society. This has important implications for asset pricing because attention is a prerequisite for distilling and processing information into prices. The underlying motivation of the empirical essays in this dissertation is to better understand the implications of boundedly rational market participants and to examine the role of limited attention. Using innovative datasets to measure attention, it provides new insights into how limited attention affects the expectation formation and behavior of financial agents, such as investors and analysts, and how this ultimately feeds into asset price dynamics. In this way, this dissertation contributes to a further development of the finance discipline from its neoclassical foundations towards a more realistic approach that integrates behavioral phenomena. In the first chapter we empirically test the rational inattention model for exchange rates. Rational inattention theory provides a framework of how cognitively limited agents might simplify and summarize available information. The framework is particularly suitable to study the relationship between exchange rates and fundamentals, because exchange rates are largely determined by expectations of market participants. Our results provide strong evidence in favor of the rational inattention theory of exchange rates. In the second chapter we examine (i) the effect of economic policy uncertainty (EPU) on the forecasts of professional equity analysts, (ii) how EPU affects analysts’ attention allocation to the overall stock market and to firm-specific news, and (iii) how EPU influences the information incorporated in stock prices. We show that periods of higher EPU are associated with higher analyst disagreement and decreased forecast accuracy. Also, analysts issue on average more pessimistic forecasts when EPU is high and ‘walk down’ their forecasts when the announcement comes closer. Second, we show that higher levels of EPU are associated with higher attention to the overall stock market, but with lower firm-level attention, and that forecast errors have a larger firm-specific component during high EPU. Finally, we demonstrate that investors do not fully unravel the decrease in forecast accuracy during high EPU, providing further evidence that investors tend to follow analyst forecasts. This has important implications for stock pricing, because when prices do not reflect the earnings news associated with the predictable component of forecast errors, the price discovery process may be affected. In the third chapter we examine the role of investor attention in the period of financial turbulence during the coronavirus pandemic. We investigate the role of what we call pandemic attention, the amount of attention paid to pandemic news, on stock markets’ behavior. We show that the allocation of attention is an important determinant of investor behavior during the pandemic, beyond health news, sentiment and other relevant factors. We show that pandemic attention has asymmetrically influenced stock market dynamics during the pandemic (negatively in bearish circumstances, positively in bullish markets). Secondly, we show that pandemic numbers and sentiment in the media covering the pandemic only had an effect on stock returns if sufficient attention was paid to it. Third, we show that higher levels of pandemic attention are associated with higher stock market volatility and comovement. Finally, we provide evidence that the higher comovement can be explained by limited attention: market participants prioritize market-wide developments above other sources of news, such that pandemic attention reduces the attention paid to firm-specific news.

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Section: Main Findingssupporting

confidence: 57%

Section: Limited Attentionmentioning

confidence: 99%

Section: Measuring Pandemic Attentionmentioning

confidence: 99%

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Limited Attention, Uncertainty, and Asset Price Dynamics

Verhoeks

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“…6 In recent literature, EDGAR search data are used in various studies focusing on the effect of information acquisition from sophisticated market participants. In this strand of literature, Li and Sun (2022) document that the investor can get an abnormal return of 8% that does not reverse in the long run by constructing a zero investment portfolio based on the attention in EDGAR. Ryans (2021) finds that EDGAR downloads of firms' comment letters can predict future earnings, the probability of restatement, and the rate of future write-downs.…”

Section: Edgar Attentionmentioning

confidence: 99%

“…, unlike market-based attention measures (e.g.,Li and Yu 2012), measures based on EDGAR attention provide us with a direct way to investigate the attention of sophisticated market participants from non-market sources McDonald 2017, Ryans 2017), which alleviates the spurious regression problem when we examine the relation between attention and other market-based variables. Second, different from information content from the supply side (Baloria and Heese 2018, Chen and Lin 2017), EDGAR attention reflect the active attention of sophisticated market participants from the demand side, which conveys additional information about markets' attitudes (e.g.,, Chen, Kelly, and Wu 2020, Drake et al 2020, Drake, Roulstone, and Thornock 2015, Li and Sun 2022. Third, apart from other platforms that offer processed information to the page viewers (e.g., Ben-Rephael, Da, and Israelsen 2017, Drake, Roulstone, and Thornock 2012), EDGAR, which contains all SEC filings of required firms, is a first-source repository for firms' information(Loughran and McDonald …”

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confidence: 99%

Three essays on corporate finance

Qu¹

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By exploiting the local randomness in close-call votes, this paper finds a causal impact of passing a governance-related proposal on the cost of stock option protection against downside tail risks. In a local regression discontinuity (RD) analysis, firms that narrowly pass the majority threshold show a lower ex-ante tail risk based on implied volatility smirk and model-free implied skewness (MFIS) than those that narrowly fail. This impact is strengthened for firms with weaker corporate governance, higher information transparency, and worse operating performance. Evidence from option trading suggests that the change in ex-ante tail risk mainly comes from trading activities in put options. In additional tests, I observe that this impact mainly comes from proposals that aim to remove management entrenchment provisions, and the impact is unique in the option market that can not be explained by realized tail risk. Evidence from financial restatement as an extreme case strengthens the link between governance proposal voting and ex-ante tail risk. Overall, this paper observes how the stock option market responds to shareholder activism through shareholder proposals and sheds light on the cross-sectional determinants of option prices.

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Machine invasion: Automation in information acquisition and the cross-section of stock returns

Pungaliya

Wang

2023

Journal of Financial Markets

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Information acquisition and expected returns: Evidence from EDGAR search traffic

Cited by 9 publications

References 64 publications

Limited Attention, Uncertainty, and Asset Price Dynamics

Limited Attention, Uncertainty, and Asset Price Dynamics

Three essays on corporate finance

Machine invasion: Automation in information acquisition and the cross-section of stock returns

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