The influence of Google search index on stock markets: an analysis of causality in-mean and variance

Mariano Gonzalez Sanchez

Review of Behavioral Finance, 2020, vol. 13, issue 2, 202-226

Abstract: Purpose - This empirical work studies the influence of investors’ Internet searches on financial markets. Design/methodology/approach - In this study, an asset pricing model with six factors is used, and autoregression, heteroscedasticity and moving average are taken into account to extract the independent shocks of each variable. Subsequently, a causality in-mean and in-variance analysis is performed to test the influence of Google searches on financial market variables, specifically, to test whether there is an influence on the idiosyncratic returns of financial assets. Findings - Unlike most of the literature, the results show that Google searches on the name of listed companies have little influence on the trend and volatility of asset returns. On the contrary, these searches are shown to have a significant influence on trading volumes in the following week. Practical implications - When analyzing specific effects, such as the influence of Internet searches, on financial markets, it is necessary that the model must include financial properties (asset valuation models) and statistical characteristics (stylized facts); otherwise, the empirical results could be inconsistent, since, among other issues, statistical findings may not be robust given autocorrelation and heteroscedasticity, and if an asset valuation model is not considered, the specific effect analyzed could simply be an indirect effect of a risk factor excluded from the model. Originality/value - The empirical evidence shows that individual investors using Google have a significant influence on volume only so that institutional investors using other sources of information drive market prices. This means that potential investors should only be interested in the Internet searches index if their interest is focused on trading volume

Keywords: Internet searching; Financial market; Spillover; Causality; G12; G14; G41 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
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: https://EconPapers.repec.org/RePEc:eme:rbfpps:rbf-01-2020-0011

DOI: 10.1108/RBF-01-2020-0011

Access Statistics for this article

Review of Behavioral Finance is currently edited by Professor Gulnur Muradoglu

More articles in Review of Behavioral Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support (feeds@emerald.com).