Employing asset-pricing models over the period 2012 to 2017, this study examines whether a search attention index (SAI) explains the variation in the weekly excess return of stocks. The study finds that the estimated abnormal return of a portfolio based on search intensity is significantly high...

We examine the effects of limited investor attention on stock returns by using Google search volume index to measure investor attention. We also investigate whether national culture and market development have any role in this relationship. We find that the impact of investor attention on stock...

This study aims at comparing Google Search Volume Indices (GSVIs—including market crash and bear market) and VIX (Investor Fear Gauge Index) in terms of explaining the S&P 500 returns. The VIX is found a more robust predictor of stock market returns than Google indices, and it does granger...

This study shows how correlated information consumption (CIC) of retail investors relates to comovement in stock market outcomes. We construct clusters of stocks with CIC by employing network analysis on Google co-search data. We predict significant comovement in returns and liquidity of stocks...

This paper examines the causal relationship between global stock market performance and Google search volume index (SVI) surrounding the disastrous event of the coronavirus (COVID-19) outbreak. Based on 6,106 stock index-day observations of 71 countries during the period from 1 January 2020 to...

The returns predictions and price movements of financial markets are predicted through online search engines. These search engines claim to trade sentiments of individual investors. This study aims to determine the changes in the American stock market returns due to Bitcoin investors’...