Measuring Investor Attention using Google Search

Management Science

76 Pages Posted: 14 Jun 2019 Last revised: 10 Feb 2024

See all articles by Ed deHaan

Ed deHaan

Stanford Graduate School of Business

Alastair Lawrence

London Business School

Robin Litjens

Tilburg University - CentER and Department of Accountancy

Date Written: February 9, 2024

Abstract

While investor attention is fundamental to the efficient functioning of capital markets, it is also an elusive construct that researchers struggle to measure. In recent years, the search volume index (“SVI”) of ticker searches on Google has become a ubiquitous measure of investor attention, but the amount and effects of measurement error in ticker SVI are unknown. We investigate measurement error in ticker SVI using a dataset of 2.7 billion website visits following S&P 500 firms’ ticker searches. We find that 69% of searches are unrelated to investing, that this measurement error is highly correlated with firm characteristics, and that this measurement error can easily generate false-positive or false-negative results in common settings. We go on to show that a modified version of SVI using both a firm’s ticker and the word “stock” (e.g., searches for “CAT stock,” which we label “ticker-stock SVI”) not only better captures the search terms that investors typically use, but also has considerably less measurement error that is largely uncorrelated with observable firm characteristics. Ticker-stock SVI produces better-specified tests and while researchers must still carefully consider the effects of measurement error, we recommend that ticker-stock SVI is used in place of ticker SVI in most settings. We provide a dataset of ticker-stock SVI to facilitate future work.



* TS-SVI data for the Russell 3000 is available for download from Robin Litjen's GitHub page and will be updated annually.



** A former working version of this paper was titled “Measurement Error in Dependent Variables in Accounting: Illustrations Using Google Ticker Search and Simulations.”

Keywords: Google ticker search; SVI; investor attention; measurement error

JEL Classification: C13, C15, M41

Suggested Citation

deHaan, Ed and Lawrence, Alastair and Litjens, Robin, Measuring Investor Attention using Google Search (February 9, 2024). Management Science, Available at SSRN: https://ssrn.com/abstract=3398287 or http://dx.doi.org/10.2139/ssrn.3398287

Ed DeHaan

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, 94305
United States

Alastair Lawrence

London Business School ( email )

Regent's Park
London
United Kingdom

HOME PAGE: http://Www.alastairlawrence.net

Robin Litjens (Contact Author)

Tilburg University - CentER and Department of Accountancy ( email )

P.O. Box 90153
Tilburg, 5000 LE
Netherlands

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