Economics at your fingertips  

Investor attention using the Google search volume index – impact on stock returns

Vighneswara Swamy () and Munusamy Dharani

Review of Behavioral Finance, 2019, vol. 11, issue 1, 55-69

Abstract: Purpose - The purpose of this paper is to investigate whether the investor attention using the Google search volume index (GSVI) can be used to forecast stock returns. The authors also find the answer to whether the “price pressure hypothesis” would hold true for the Indian stock market. Design/methodology/approach - The authors employ a more recent fully balanced panel data for the period from July 2012 to Jun 2017 (260 weeks) of observations for companies of NIFTY 50 of the National Stock Exchange in the Indian stock market. The authors are motivated by Tetlock (2007) and Bijl Findings - The authors find that high Google search volumes lead to positive returns. More precisely, the high Google search volumes predict positive and significant returns in the subsequent fourth and fifth weeks. The GSVI performs as an useful predictor of the direction as well as the magnitude of the excess returns. The higher quantiles of the GSVI have corresponding higher excess returns. The authors notice that the domestic investor searches are correlated with higher excess returns than the worldwide investor searches. The findings imply that the signals from the search volume data could be of help in the construction of profitable trading strategies. Originality/value - To the best of the authors knowledge, no paper has examined the relationship between Google search intensity and stock-trading behavior in the Indian stock market. The authors use a more recent data for the period from 2012 to 2017 to investigate whether search query data on company names can be used to predict weekly stock returns for individual firms. This study complements the prior studies by investigating the relationship between search intensity and stock-trading behavior in the Indian stock market.

Keywords: Stock returns; Predictability; Google searches; G11; G12; G14 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) ... RePEc&WT.mc_id=RePEc (text/html)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK
http://emeraldgroupp ... /journals.htm?id=rbf

Access Statistics for this article

Review of Behavioral Finance is currently edited by Phil Holmes and Robert Hudson

More articles in Review of Behavioral Finance from Emerald Group Publishing
Bibliographic data for series maintained by Virginia Chapman ().

Page updated 2021-05-20
Handle: RePEc:eme:rbfpps:rbf-04-2018-0033