High Frequency and Unstructured Data in Finance: An Exploratory Study of Twitter

INTRODUCTION " Breaking: Two Explosions in the White House and Barack Obama is injured. " (The Associated Press, 10:07, April 23rd 2013) 72 characters later, the S&P500 index lost more than 121 billion US dollars until the tweet was proven false and confirmed to be sent by a hacked Associated Press account. A 1.68 billion-dollar bill for each character written. However, this particular event shed light on the implication of spreading news on the stock markets, especially through social media. Our research question is to know whether information running through Twitter explain some of the stock price variations on the S&P500. Twitter is a new way of spreading information, not only through short sentences, but also by allowing users to emphasize one particular piece of information by retweeting. As such, is Twitter a complement to traditional ways of spreading news, or is it a revolution? Applied to a particular market-the financial market-this question takes a whole different dimension. Indeed, information is at the core of finance. In theory, there is no way to beat the market return. However, when one investor has more information than another one, then she can beat the market. In this regard, can we extract some extra information from messages on Twitter that can lead to some investors beating the market all the time? Since the advent of modern finance, information has taken a central role in every mechanism of the industry. While Markowitz established the theoretical framework upon which relies the Capital Asset Pricing Model, strong assumptions have been made. Among them figures the fact that an investor will act in a rational way in order to maximize her returns while minimizing her risks [1]. Twenty years later, [2] characterized the market efficiency regarding information: there should be no gain opportunity on the stock markets because they are defined by random walk patterns, while all information is known at any time because prices instantly reflect new events. These two assumptions have shown their limitations, especially