How Wise Are Crowds? Insights from Retail Orders and Stock Returns

Kelley, Eric K.; Tetlock, Paul C.

doi:10.1111/jofi.12028

Cited by 387 publications

(127 citation statements)

References 67 publications

(132 reference statements)

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“…The positive relationship between individual investors and PIN seems puzzling because the former have been regarded as uninformed traders due to behavioral biases (Barber and Odean, 2000), noise trading (Foucault et al, 2011) and the lack of information advantage about local stocks (Seasholes and Zhu, 2010). However, there is growing empirical evidence that individual investors possess valuable private information and engage in informed trading (Kelley and Tetlock, 2013;Fong et al, 2014a;Tian et al, 2015). This possibility of individuals having private information cannot be ruled out in the context of Malaysia, given the prevalence of ownership concentration in the hands of family (see Carney and Child, 2013).…”

Section: Estimation Results and Discussionmentioning

confidence: 99%

Corporate Shareholdings and the Liquidity of Malaysian Stocks: Investor Heterogeneity, Trading Account Types and the Underlying Channels

2015

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Abstract:This paper examines the relationship between shareholdings of various investor groups and stock liquidity for Malaysian public listed firms over the [2002][2003][2004][2005][2006][2007][2008][2009] sample period. Using the Amihud illiquidity ratio, we extend the literature by addressing the issues of investor heterogeneity, trading account types and the interactions of competing liquidity channels. The analysis reveals that only local institutions and local individual investors who trade through the direct accounts are significantly associated with the liquidity of domestic firms. In contrast, the significant liquidity effect for foreign investors operates through the nominee accounts. While institutional ownership exhibits a linear negative relationship, our findings on local individuals and foreign nominees differ greatly from previous studies in that their relationship with stock liquidity is non-monotonic. Apart from the widely researched information asymmetry and trading effects, we find that liquidity is also driven by the largely ignored information competition channel. An important insight from our findings is that the large shareholdings by any particular investor group is detrimental to stock liquidity as they exacerbate information asymmetry, reduce the degree of competition and lower the level of trading activity.JEL Classifications: G12; G32

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Section: Estimation Results and Discussionmentioning

confidence: 99%

Corporate Shareholdings and the Liquidity of Malaysian Stocks: Investor Heterogeneity, Trading Account Types and the Underlying Channels

2015

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“…Previous research shows that the tone in newspaper columns drives investor sentiment (Tetlock, 2007;Garcia, 2013), captures information beyond fundamentals (Tetlock, Saar-Tsechansky, and Macskassy, 2008) and affects individual trading behaviour (Kelley and Tetlock, 2013). Moreover, the tone of news can be improved by increasing local advertising spending (Gurun and Butler, 2012) and hiring investor relationship firms (Solomon, 2012).…”

Section: Introductionmentioning

confidence: 99%

Media Content and Stock Returns: The Predictive Power of Press

Ferguson¹,

Philip²,

Lam³

et al. 2015

MFJ

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Jie Michael Guo Durham Univercity Business School, UKThis paper examines whether tone (positive and negative) and volume of firm-specific news media content provide valuable information about future stock returns, using UK news media data from 1981-2010. The results indicate that both tone and volume of news media content significantly predict next period abnormal returns, with the impact of volume more pronounced than tone. Additionally, the predictive power of tone is found to be stronger among lower visibility firms. Further, the paper finds evidence of an attention-grabbing effect for firm-specific news stories with high media coverage, mainly seen among larger firms. A simple news-based trading strategy produces statistically significant risk-adjusted returns of 14.2 to 19 basis points in the period [2003][2004][2005][2006][2007][2008][2009][2010]. At the aggregate level, price pressure induced by semantics in news stories is corrected only in part by subsequent reversals. Overall, the findings suggest firm-specific news media content incorporates valuable information that predicts asset returns. (JEL: G1, G14, G17)

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“…S ince Galton's discovery of the "wisdom of crowds" over 100 years ago (1), results on crowdsourcing (1, 2), prediction markets (3), and financial forecasting (4,5) have shown that the aggregated judgment of many individuals can be more accurate than the judgments of individual experts (2,4,(6)(7)(8). Statistical explanations for this phenomenon argue that group accuracy relies on estimates taken from groups where individuals' errors are either uncorrelated or negatively correlated, thereby preserving the diversity of opinions in a population (9).…”

mentioning

confidence: 99%

Network dynamics of social influence in the wisdom of crowds

Becker

Brackbill

Centola

2017

Proc. Natl. Acad. Sci. U.S.A.

325

258

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A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton's discovery of the "wisdom of crowds" [Galton F (1907 social networks | collective intelligence | social learning | wisdom of crowds | experimental social science S ince Galton's discovery of the "wisdom of crowds" over 100 years ago (1), results on crowdsourcing (1, 2), prediction markets (3), and financial forecasting (4, 5) have shown that the aggregated judgment of many individuals can be more accurate than the judgments of individual experts (2, 4, 6-8). Statistical explanations for this phenomenon argue that group accuracy relies on estimates taken from groups where individuals' errors are either uncorrelated or negatively correlated, thereby preserving the diversity of opinions in a population (9). Thus, although individuals may have estimates both far above and far below the true value, in aggregate these errors cancel out, leaving an accurate group judgment (2, 9, 10).Recent experimental evidence has suggested that the wisdom of crowds may be undermined by processes of social influence, in which people exchange information about their estimates and revise their judgments to align with one another (11-13). When social influence leads to correlated errors, both independence and diversity are reduced, which has been argued to compromise the reliability of the group judgment (9,(11)(12)(13)(14)(15)(16)(17)(18). In direct contrast with these results, however, theoretical models of social learning (19-21) have suggested that the effects of social influence on collective decisions vary based on the structure of the interaction network, predicting that, under the right conditions, social learning can lead a group's median judgment to improve (20)(21)(22)(23)(24).This prediction derives from the assumption that, when people learn about the beliefs of others, they revise their own beliefs to become more similar to their social referents (11, 12, 25, 26). Following the DeGroot model of social learning, this theory suggests that each individual's revisions are based on a weighted average of their own belief and the beliefs of their social referents (19). Thus, an individual's revision is determined in part by the amount of weight they place on their own belief relative to social information. When this "self-weight" is independently and identically distributed (i.i.d.) throughout a population, and the population is embedded in a decentralized social network (i.e., one in which everyone is equally connected), this model predicts that belief distributions will converge on the statistical mean of the initial, independent beliefs (SI Appendix). Thus, if the initial group mean is accurate, exposure to social influence will lead individuals in the group to become more accurate, improving the accuracy of the group's median, even as the group mean remains fixed (SI Appendix).We build on the DeGroot model to generate theoretical predictions ...

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How Wise Are Crowds? Insights from Retail Orders and Stock Returns

Cited by 387 publications

References 67 publications

Corporate Shareholdings and the Liquidity of Malaysian Stocks: Investor Heterogeneity, Trading Account Types and the Underlying Channels

Corporate Shareholdings and the Liquidity of Malaysian Stocks: Investor Heterogeneity, Trading Account Types and the Underlying Channels

Media Content and Stock Returns: The Predictive Power of Press

Network dynamics of social influence in the wisdom of crowds

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