Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 27, Issue 4, Pages 1116-1127Publisher
ELSEVIER
DOI: 10.1016/j.ijforecast.2010.11.001
Keywords
Investor sentiment; Finance; Fama-French model; Portfolio tests; Marketing
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We examine the ability of online ticker searches (e.g. XOM for Exxon Mobil) to forecast abnormal stock returns and trading volumes. Specifically, we argue that online ticker searches serve as a valid proxy for investor sentiment - a set of beliefs about cash flows and investment risks that are not necessarily justified by the facts at hand - which is generally associated with less sophisticated, retail investors. Based on prior research on investor sentiment, we expect online search intensity to forecast stock returns and trading volume, and also expect that highly volatile stocks, which are more difficult to arbitrage, will be more sensitive to search intensity than less volatile stocks. In a sample of S&P 500 firms over the period 2005-2008, we find that, over a weekly horizon, online search intensity reliably predicts abnormal stock returns and trading volumes, and that the sensitivity of returns to search intensity is positively related to the difficulty of a stock being arbitraged. More broadly, our study highlights the potential of employing online search data for other forecasting applications. (C) 2011 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
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