Hailiang Chen, Prabuddha De, Yu Jeffrey Hu, and Byoung-Hyoun Hwang
Wisdom of crowds: The value of stock opinions transmitted through social media
Review of Financial Studies | Volume 27, Issue 5 (May 2014), 1367–1403

In recent years, with the rapid development of social media, investors have begun conducting their own equity research and sharing their financial analysis of stocks with others on social media. In some cases, these reports are remarkably insightful.

Crowd-sourced stock analyses and opinions

For example, on March 17, 2011 a blogger using the pseudonym Alfred Little published an article about Deer Consumer Products Inc. (DEER) on the crowd-sourced investment research site Seeking Alpha. Based on his/her own research, the blogger claimed that the U.S.-listed Chinese producer of small kitchen appliances had inflated its sales and profit margins and overpaid for land purchases. In three months, the share price of DEER fell by approximately 40%; the stock was eventually delisted from Nasdaq in March 2013 for committing fraud.

In the context of the rapid growth of social media outlets specializing in financial markets, such anecdotal accounts pose an interesting question: Are stock opinions revealed on social media sites valuable, on average, to investors? Arguably, the openness and lack of regulation inherent in social media outlets imply that uninformed actors can easily spread erroneous “information” among market participants. Regulators also warn that e-mail and social media are increasingly used to pump and dump micro-cap stocks in the Internet age. At the same time, it is plausible that large crowds possess valuable information, particularly for stocks neglected by professional analysts and traditional media. Even for stocks covered by sell-side analysts, it is possible that the crowd sometimes conveys insights that are valuable yet not fully factored into sell-side analysts' earnings forecasts and recommendations. Moreover, financial analysts' jobs are fraught with built-in conflicts of interest and competing pressures. In Chen-De-Hu-Hwang (RFS 2014), we assess the performance of investors-turned-advisors and test whether investors can turn to their peers for truly useful investment advice.

Seeking Alpha

To examine the role of peer-based advice, we select Seeking Alpha (SA), one of the largest investment-related social-media websites in the United States, as our data source. Investors can voice their opinions and exchange investment ideas on this site through two channels: (a) Users can submit opinion articles to SA, which are generally reviewed by a panel and subject to editorial changes. If deemed of adequate quality, these articles are then published on the SA website. (b) In response to published articles, any interested user can write a commentary, sharing his or her own view, which may agree or disagree with the author's view on the company in question. Over our 2005-2012 sample period, SA articles and SA commentaries were written by approximately 6,500 and 180,000 users, respectively, covering more than 7,000 firms.

Wisdom of crowds

To quantify the views disseminated through SA, we employ textual analysis and use the frequency of negative words employed in an article/commentary to capture its tone. Our analyses show that the fraction of negative words contained in SA articles and the fraction of negative words in SA commentaries both negatively predict stock returns over the ensuing three months. We obtain similar results over one-month, six-month, one-year, and three-year horizons. Figure 1 plots the coefficient estimates, along with the corresponding 95% confidence intervals, from regressions of abnormal returns on measures of the views reflected in SA articles and commentaries.

1: Seeking Alpha and abnormal returns over various holding periods
Panel A: Coefficient estimate on views in SA articles






Panel B: Coefficient estimate on views in SA commentaries





The are coefficient estimates and 95% confidence intervals from regressions of abnormal returns on measures of the views reflected SA articles and commentaries from 2005-2012.

One interpretation of our findings is that the views expressed in SA articles and SA commentaries contain some value-relevant information, which, as of the article publication date, is not fully factored into the price. As investors subsequently adopt the SA view, either through the SA platform itself or through news that arrives following the article publication, the price gradually adjusts. Such an interpretation would point to the usefulness of social media outlets as a source of genuine, value-relevant advice.

An alternative perspective is that SA views produce naive investor reactions. That is, SA views often reflect false or spurious information that nevertheless causes investors to trade in the direction of the underlying articles and commentaries and move prices accordingly. Our methodology (skipping the first two days after article publication and focusing on a three-month horizon) and our observed lack of a return reversal are somewhat at odds with this interpretation. Moreover, it is doubtful that followers of SA have enough capital of their own to cause market prices to move in the manner that we document in this study.

We also examine whether SA views predict subsequent earnings surprises, which is the difference between the reported earnings-per-share (EPS) and the average of financial analysts' EPS forecasts. If opinions expressed through SA that we observed were unrelated to firms' fundamentals or if the information was spurious and already fully incorporated by financial analysts into their reported EPS forecasts, then no association should be observed between our earnings-surprise variable and our measure of peer-based advice. In contrast, we find that the fraction of negative words in SA articles and commentaries strongly predict subsequent earnings surprises.


How does the “wisdom of crowds” work in the domain of stock analyses and opinions? We provide empirical evidence along two channels. We first construct, for each author, a measure of historical consistency. Our measure captures the degree to which predominantly positive (predominantly negative) articles by the author in question are subsequently followed by positive (negative) abnormal returns.

Our first analysis shows that both the number of page views, which directly impacts the level of monetary compensation the author receives from SA, and the number of times an article is read to the end, increase with the author's historical level of consistency. This pattern suggests that followers can differentiate between authors who offer historically good advice versus those who offer historically bad advice and the “popularity” of these authors changes accordingly. This should motivate authors to provide good and honest advice.

Our second analysis computes the degree to which SA commentaries on an underlying SA article convey a tone that contrasts with that of the SA article, and we relate this measure of author/follower disagreement to the author's historical track record. Our evidence implies that followers disagree with authors to a greater extent when the authors' articles have been inconsistent in the past. For these historically inconsistent authors, our evidence also suggests that in instances where the tone of commentaries disagrees with the tone of the underlying article, it is the tone of the commentaries that more reliably predicts subsequent stock market performance. In other words, it appears that another reason social media works in the domain of stock analyses is the “social aspect,” which creates diversity of opinions and corrects/discourages the involvement of malignant and uninformed contributors.


Our paper assesses the value relevance of stock analyses and opinions shared by investors on social media. Traditionally, the job of financial forecasting has been performed by highly paid professional analysts; in recent years, do-it-yourself (DIY) financial analysis has become a trend, and investors are adopting social media to publicize their research work. In a National Examination Risk Alert, the U.S. Securities and Exchange Commission stated that “social media is landscape-shifting.” Our study is an initial attempt to investigate the role of the evolving social media phenomenon in financial markets. There are many opportunities for future research in this area.