Google searches and stock returns

Laurens Bijl, Glenn Kringhaug, Peter Molnár and Eirik Sandvik

International Review of Financial Analysis, 2016, vol. 45, issue C, 150-156

Abstract: We investigate whether data from Google Trends can be used to forecast stock returns. Previous studies have found that high Google search volumes predict high returns for the first one to two weeks, with subsequent price reversal. By using a more recent dataset that covers the period from 2008 to 2013 we find that high Google search volumes lead to negative returns. We also examine a trading strategy based on selling stocks with high Google search volumes and buying stocks with infrequent Google searches. This strategy is profitable when the transaction cost is not taken into account but is not profitable if we take into account transaction costs.

Keywords: Stock returns; Google searches; Predictability (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (108)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:45:y:2016:i:c:p:150-156

DOI: 10.1016/j.irfa.2016.03.015

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