“Talk is cheap, particularly on the Internet. Stock message boards are a case in point. Every day participants post tens of thousands of tips about which way various stocks are heading. Is any of this worth reading?” writes Hal Varian in today’s New York Times.

“Recently, two financial economists from the University of British Columbia, Werner Antweiler and Murray Z. Frank, examined the message board phenomenon in a paper entitled ‘Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards,’ published in the June 2004 issue of The Journal of Finance.”

“They collected more than 1.5 million messages from two online boards, Yahoo Finance and Raging Bull, and analyzed them using methods of computational linguistics and econometrics.”

“The computational linguistics techniques allowed them to classify messages with respect to whether they advocated buying, holding or selling the stock in question. Most of the messages were short and direct, allowing the algorithms to do a pretty good job of classification.”

“Of course, some postings could not be easily classified. As the authors charitably remark, ‘A remarkable range of sometimes quite odd things are said in the messages.’ ”

“Mr. Antweiler and Mr. Frank then merged the estimated buy/sell/hold signals into one ‘bullishness measure,’ which was a slightly modified version of the ratio of buy to sell recommendations.”

“During the period they examined in their article, January to December 2000, the Internet bubble dissipated. Bullish messages, however, continued to proliferate throughout the year, perhaps reflecting a ‘buy on the dips’ sentiment popular at the time. Or perhaps the messages represented attempts by day traders to talk up the value of the stocks in their dwindling portfolios.”

“But did the message volume, timing and sentiment forecast anything useful? The three most interesting features of a stock on a given day are its return (how much it increased or decreased), its volume (how many shares were traded) and its volatility (how much the price fluctuated).”

“The authors found that the characteristics of messages helped predict volume and volatility. Perhaps more surprisingly, they also found that the number of messages on one day helped predict stock returns the next day. The degree of predictability, however, was weak and reversed itself the next trading day. Perhaps cheap talk can move stock prices a tiny bit, but if so, the response was only temporary.”