It is clear to even the most casual investor that stock prices often move for irrational reasons. In general, this is because the stock market is driven by human action and naturally reflects the chronic irrationality within human nature.1 The efficient market hypothesis is a pleasant academic fiction, although successful investing requires being mindful of the inefficient (or, say, “sentimental”) factors that lurk beneath. To understand and harness the power of sentiment for profit has been a long-time dream of money managers. The subjective nature of what constitutes sentiment is a serious impediment to the realization of this dream; however, recent technological advances in the field of computational linguistics provide opportunities to approach the matter in a more rigorous, objective way. Leveraging the most up-to-date technology, we attempt to measure the sentiment around companies as determined by their news coverage and incorporate such measurements into a profitable investment strategy.

Notable contributions to the understanding of news sentiment are to be found throughout the academic landscape. The media effect is one of the better known empirical results connecting news and stock returns; viz., companies with no media coverage outperform companies with high media coverage. In Fang and Peress (forthcoming) and Peress (2008), the case is made that media coverage is directly related to the pricing of information risk, hence the companies that are not covered ...

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