scholarly journals Donald Trump, investor attention and financial markets

2020 ◽  
Author(s):  
Tapas Tanmaya Mohapatra ◽  
Monika Gehde-Trapp
Keyword(s):  
Financial Markets ◽  
Volume Index ◽  
Investor Attention ◽  
Wealth Transfer ◽  
Search Volume ◽  
Retail Investors ◽  
Retail Investor ◽  
Google Search ◽  
Source Of Information ◽  
Sheer Number

Information attracts attention but attention is costly. Social media has been at the forefront ofinformation dissipation due to the sheer number of users propagating information in a fast but cheap way. We look into one specific case where Donald Trump’s tweets on companies have had effect on retail investors whose only source of information is internet. We find that retail investor attention spike as indicated by surge in Google Search Volume Index following Donald Trump’s tweet, irrespective of the tone in the tweet. We also find that Trump’s tweet facilitates wealth transfer due to selling from the retail investors followed by buying by the institutional investors in low retail investor attention environment. Finally, we see no effect in intra-day returns for the stocks irrespective of the attention they are receiving.

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

2019 ◽  
Vol 11 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Vighneswara Swamy ◽  
Munusamy Dharani
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Volume Index ◽  
Trading Behavior ◽  
Excess Returns ◽  
Investor Attention ◽  
Content Type ◽  
Search Volume ◽  
Indian Stock Market ◽  
Google Search

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 et al. (2016) to employ regression approach of econometric estimation. 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.

scholarly journals The time-varying causal relationship between the Bitcoin market and internet attention

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xun Zhang ◽  
Fengbin Lu ◽  
Rui Tao ◽  
Shouyang Wang
Keyword(s):  
Causal Relationship ◽  
Granger Causality ◽  
Trading Volume ◽  
Volume Index ◽  
Time Varying ◽  
Investor Attention ◽  
Empirical Results ◽  
Search Volume ◽  
Google Search ◽  
Shed Light

AbstractThe increasing attention on Bitcoin since 2013 prompts the issue of possible evidence for a causal relationship between the Bitcoin market and internet attention. Taking the Google search volume index as the measure of internet attention, time-varying Granger causality between the global Bitcoin market and internet attention is examined. Empirical results show a strong Granger causal relationship between internet attention and trading volume. Moreover, they indicate, beginning in early 2018, an even stronger impact of trading volume on internet attention, which is consistent with the rapid increase in Bitcoin users following the 2017 Bitcoin bubble. Although Bitcoin returns are found to strongly affect internet attention, internet attention only occasionally affects Bitcoin returns. Further investigation reveals that interactions between internet attention and returns can be amplified by extreme changes in prices, and internet attention is more likely to lead to returns during Bitcoin bubbles. These empirical findings shed light on cryptocurrency investor attention theory and imply trading strategy in Bitcoin markets.

scholarly journals Effect of Online Searches on Stock Returns

2017 ◽  
Vol 7 (1) ◽  
pp. 70
Author(s):  
Saurabh Ahluwalia
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Information Seeking ◽  
Volume Index ◽  
Information Seeking Behavior ◽  
Data Set ◽  
Search Volume ◽  
Retail Investors ◽  
Seeking Behavior ◽  
Google Search

Various theoretical models assume that information seeking behavior of investors has an impact on prices. However, it is very difficult to empirically test this, since the actual information acquisition process of the investors is unobservable. Using a unique data set from Google Trends, I construct a search volume index (SVI) and use it to proxy for the information seeking behavior of retail investors. Using a portfolio based approach I document the asymmetric response of future returns to the changes in the google search volume. I find that the portfolio with the highest increase in the SVI has positive and significant alphas while portfolios with decrease in SVI show no significant results.  My results are robust to alternative specifications of risk models, time frames and measures of search index. Overall, my results are in line with the hypothesis that retail investors’ trades can effect stock prices.  

Attention to Global Warming

2020 ◽  
Vol 33 (3) ◽  
pp. 1112-1145 ◽  
Author(s):  
Darwin Choi ◽  
Zhenyu Gao ◽  
Wenxi Jiang
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Financial Markets ◽  
Low Carbon ◽  
Search Volume ◽  
Warm Weather ◽  
Collective Beliefs ◽  
Retail Investors ◽  
International Data ◽  
Google Search

Abstract We find that people revise their beliefs about climate change upward when experiencing warmer than usual temperatures in their area. Using international data, we show that attention to climate change, as proxied by Google search volume, increases when the local temperature is abnormally high. In financial markets, stocks of carbon-intensive firms underperform firms with low carbon emissions in abnormally warm weather. Retail investors (not institutional investors) sell carbon-intensive firms in such weather, and return patterns are unlikely to be driven by changes in fundamentals. Our study sheds light on peoples’ collective beliefs and actions about global warming.

Investors’ Attention and American Depository Receipts Pricing: Evidence from Indian Stocks

2019 ◽  
Vol 9 (12) ◽  
pp. 381-386
Author(s):  
A Sarath Babu
Keyword(s):  
Volume Index ◽  
American Depository Receipts ◽  
Control Variables ◽  
Search Volume ◽  
Depository Receipts ◽  
Book To Market Ratio ◽  
Google Search ◽  
The Impact

This paper is an attempt to examine the impact of investors’ attention on returns and the traded volume of American Depository Receipts prices for selected ten Indian Stocks. The Google search volume index has been used as a proxy for investors’ attention in this paper. However, factors such as size and book to market ratio were used to indicate as control variables. The results reveal that investors’ attention variable significantly affects ADRs traded volume, but has no impact on the ADR prices.

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