Social media sentiment can predict fluctuations in stock market volume as much as six to seven days ahead of time, according to a Harvard Business School doctoral candidate who has been studying the impact social media has on equities.

That could become a valuable tool for hedge funds and investment firms. High volatility often makes it easier for firms to trade stocks. Volatility predictions can also be factored into more comprehensive trading models and better predict whether a stock's price will rise or fall.

Frank Nagle is still working on his research but so far his findings echo those of other people who have looked at the issue. Most notably, what people say about a brand on social media is often a better indicator of how a stock will perform than what people say on social media about an individual stock.

"As far back as six or seven days, people's perceptions of a brand matter," Nagle said. "The problem has been that public perception has always taken longer than a buy or sell sentiment to factor into share price."

Nagle's research also shows in certain concentrated industries sentiment about the overall industry may have more of an impact on share price than sentiment about the individual company. He offered the airline industry as an example, where a relatively small number of publicly-traded companies focus on providing one core service. An increases in tweets about air travel, for example, may predict forthcoming volatility for the volume of shares for companies within that industry.

Nagle cautioned that, at least for now, social media sentiment is probably not enough to make an educated buy or sell decision, but it can - and will - be a factor in trading models going forward.

"It's useful to know what the public is saying about a company to help make those decisions, and theoretically using that data to make those decisions could be possible in the future," he said. "But for now, if the only piece of information you're using to make buy and sell decisions is social media, I would be concerned."

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