Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257801 
Year of Publication: 
2021
Citation: 
[Journal:] International Journal of Financial Studies [ISSN:] 2227-7072 [Volume:] 9 [Issue:] 4 [Article No.:] 56 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-20
Publisher: 
MDPI, Basel
Abstract: 
The purpose of this study is to investigate the fluctuations that occur in stock returns of US stock indices when there is an increase in the volume of Google internet searches for the phrase "quantitative easing" in the US. The exponential generalized autoregressive conditional heteroscedasticity model (EGARCH) was applied based on weekly data of stock indices using the three-factor model of Fama and French for the period of 1 January 2006 to 30 October 2020. The existence of a statistically significant relationship between searches and financial variables, especially in the stock market, is evident. The result is strong in three of the four stock indices studied. Specifically, the SVI index was statistically significant, with a positive trend for the S&P 500 and Dow Jones indices and a negative trend for the VIX index. Investor focus on quantitative easing (QE), as determined by Google metrics, seems to calm stock market volatility and increase stock returns. Although there is a large body of research using Google Trends as a crowdsourcing method of forecasting stock returns, this paper is the first to examine the relationship between the increase in internet searches of "quantitative easing" and stock market returns.
Subjects: 
crowdsourcing
EGARCH
Google Trends
quantitative easing
stock indices
three-factor model
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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