Measuring Investor Attention Using Google Search

Abstract

Although 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 data set of 2.7 billion website visits following Standard and Poor’s 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 although 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 data set of ticker-stock SVI to facilitate future work. This paper was accepted by Suraj Srinivisan, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02174 . TS-SVI for the Russell 3000 is available for download at: github.com/robinlitjens/GoogleTickerStock-SVI and will be updated annually.