The notion that the collective wisdom of the crowd is superior to that of any individual is well-documented. Here's one of the classic wisdom-of-the-crowd findings:
At a 1906 country fair, eight hundred people participated in a contest to estimate the weight of a slaughtered and dressed ox. Statistician Francis Galton observed that the median guess, 1207 pounds, was accurate within 1% of the true weight of 1198 pounds.
This concept, as I discussed in a recent article, shaped Seeking Alpha's vision of being an open, curated platform for diverse stock-market opinion, in which all sides have a say, and in which the audience plays a key role in the discussion.
But investors care more about results than they do about noble visions, which prompts the question: Is crowd-sourcing predictive of future returns within the sophisticated arena of stock investing, or are above-average returns the domain of a few gurus?
A recent academic study highlighted in today's Wall Street Journal puts that question to rest: Seeking Alpha outperforms broader markets, the sell-side, financial media, and other social platforms over every time frame studied.
Here's what the Journal has to say (with light edits for brevity/clarity):
A new academic study lends credence to the idea that the “wisdom of crowds” phenomenon applies not just to encyclopedia entries and restaurant reviews, but also to stock market predictions.
Researchers from City University of Hong Kong, Purdue University and Georgia Institute of Technology found that the tone of stock market opinion blogs published on investor forum seekingalpha.com predicted stock returns, as well as earnings surprises, above and beyond what was evident from Wall Street analyst reports and financial news articles.
Seekingalpha.com is a forum for investors who write opinion pieces about stocks for the site. An editorial board vets the quality of the blogs and posts up to 250 articles every day.
Researchers analyzed about 100,000 Seeking Alpha articles and commentary published between 2005 and 2012 for the paper “Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media,” which is forthcoming in the Review of Financial Studies.
The potential to discover market-predicting information in social media has been tantalizing to investors big and small. Several startups, including companies like Dataminr, Gnip and DataSift, have talked about providing feeds of Twitter and other social-media outlets to hedge funds and other money managers to inform their investment strategies. But the connection between what’s happening on social media and what’s happening on the stock market has had little proof to date. One study showed that the general mood of the public, as exhibited in aggregate tweets, can predict the movements in the Dow Jones Industrial Average. That study didn’t look at individual stocks, but the new study did.
“Seeking Alpha is the only platform to date that we have shown can predict individual stock returns,” said Yu Jeffrey Hu, associate professor at Georgia Tech’s Scheller College of Business and one of the authors of the study. Other authors of the study are Hailiang Chen, Prabuddha De, and Byoung-Hyoun Hwang.
Dr. Hu said that research was in no way sponsored or facilitated by Seeking Alpha. The company did provide a proprietary data stream for one portion of the research, he said.
The researchers looked for the fraction of negative words in the articles and commentary on a particular stock on a particular date, and then tracked the performance of the stock after the blog publication. It turned out that the more negative the blogs and blog comments were on a stock, the more likely the stock was to perform worse than similar stocks in the next several months. Similarly, the negative tone of Seeking Alpha articles predicted earnings surprises, which are the earnings results reported by companies relative to the average of analysts’ earnings forecasts.
“We cannot say this particular stock will go up or down in absolute. But it will perform better than a portfolio of roughly similar stocks,” Dr. Hu said.
The researchers created a virtual investment strategy where they went long on stocks most liked and went short on stocks most disliked by the Seeking Alpha community, and showed a multi-year return of some 40%, Dr. Hu said. Notably, the virtual profit kept growing through the 2008 market crash.
Does this mean sell-side financial analysts are useless? “I wouldn’t say [Seeking Alpha blog writers] are absolutely better than the highly paid Wall Street analysts,” Dr. Hu said. But “Seeking Alpha sentiment has additional insight above and beyond financial Wall Street analysts,” Dr. Hu said.
The researchers also noted that Seeking Alpha predicted stock returns above what was evident from news articles. The report used news stories published on Dow Jones News Service, which is a part of Dow Jones & Co., publisher of The Wall Street Journal. Dow Jones declined to comment.
Overall, the findings fit with prior analysis in other fields on the way crowds can outsmart, or at least be just as smart, as professionals. Studies have shown, for example, that Wikipedia accuracy is similar to that of Encyclopedia Britannica.
Crowd platforms have other advantages over professionals, besides accuracy - Seeking Alpha, for example, covers a greater stock universe than stock analysts, and Wikipedia has more subject entries than Encyclopedia Britannica. Plus, both get updated and revised as things change more quickly than their professional counterparts, Dr. Hu said.
“It’s clear that we’re sitting on valuable data,” Seeking Alpha CEO David Jackson said. “We need to mine and share more data about what the community is thinking and doing.”
The article doesn't fully describe something I found remarkable: The researchers looked at pageviews and reads-to-end (how many readers finished reading an article) for articles that were destined to be predictive of future returns, and for articles that were destined to be counter-predictive of future returns. They also measured the acrimoniousness of those articles' comments. They found, astonishingly, that during the first 48 hours after publication, articles that were destined to be predictive of future returns had above average page-views, above average reads-to-end, and unacrimonious comment streams, while articles that were destined to be counter-predictive had below average page-views, below average reads-to-end, and acrimonious comment streams. In other words, crowd behavior was a leading indicator of which predictions would be right, and which would be wrong.
Other points from the study that weren't obvious from the Journal article:
Hats off to David Jackson, our CEO, for having the vision to build such a powerful platform. And to everyone inside Seeking Alpha who works tirelessly to make SA a great website. But most of all, to our contributors and readers: this study is a validation of the collective wisdom you provide that makes us all smarter investors.
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