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 Investor attention and the response of US stock market sectors to the COVID-19 crisis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lee A. Smales
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Information Discovery ◽  
Investor Attention ◽  
Content Type ◽  
Search Volume ◽  
Global Stock Markets ◽  
Google Search ◽  
The Relationship ◽  
Global Stock

PurposeCOVID-19 has had an immense impact on global stock markets, with no sector escaping its effects. Investor attention towards COVID-19 surged as the virus spread, the number of cases grew and its consequences imposed on everyday life. We assess whether this increase in investor attention may explain stock returns across different sectors during this unusual period.Design/methodology/approachWe adopt the methodology of Da et al. (2015), using Google search volume (GSV) as a proxy for investor attention to examine the relationship between investor attention and stock returns across 11 sectors.FindingsOur results demonstrate that heightened attention towards COVID-19 negatively influences US stock returns. However, relatively speaking, some sectors appear to have gained from the increased attention. This outperformance is centred in the sectors most likely to benefit (or likely to lose least) from the crisis and associated spending by households and government (i.e. consumer staples, healthcare and IT). Such results may be explained by an information discovery hypothesis in the sense that investors are searching online for information to enable a greater understanding of COVID-19's impact on relative stock sector performance.Originality/valueWhile we do not claim that investor attention is the only driver of stock returns during this unique period, we do provide evidence that it contributes to the market impact and to the heterogeneity of returns across stock market sectors.

scholarly journals The Effect of Google Search Volume Index on the Stock Market Excess Returns. Evidence from Listed firms in Pakistan stock Exchange

2021 ◽  
Vol 4 (1) ◽  
pp. 23-35
Author(s):  
Bushra Ayaz ◽  
Hamid Ullah ◽  
Muhammad Kamran Khan ◽  
Shahid Jan
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Developed Countries ◽  
Volume Index ◽  
Large Sample Size ◽  
Trading Behavior ◽  
Excess Returns ◽  
Listed Firms ◽  
Search Volume ◽  
Google Search

The aim of this study is to examine whether google search volume index (GSVI) as a tool of investor’s attentions can be of great used to forecast stock returns. In this paper we answer the question whether “price pressure hypothesis “would hold true for Pakistan stock markets. The nature of current study is quantitative in nature and research design is used to test the hypothesis developed to examine google search volume index and stocks return behavior. We used balanced panel data for the period from 2003 to 2019 for companies listed in Pakistan stock exchange. In this paper, we use regression technique for econometrics estimation. The results showed that high and a positive return is associated with high google search volume. To be more accurate, we can say that a google search volume index is an important and useful predictor for both the directions and magnitude of excess returns. We suggest that, this study will be helpful for the information of profitable trading strategies. With this study, we complement all previous work done in developed countries on the correlation between stock trading behavior and search intensity by using more robust statistical techniques and large sample size.

Investor attention and market correction

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhongdong Chen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Behavior ◽  
Investor Attention ◽  
Information Effect ◽  
Content Type ◽  
Economic Significance ◽  
New Information ◽  
Positive Volume ◽  
The Impact

PurposeThis study disentangles the investor-base effect and the information effect of investor attention. The former leads to a larger investor base and higher stock returns, while the latter facilitates the dissemination of information among investors and impacts informational trading.Design/methodology/approachUsing positive volume shocks as a proxy for increased investor attention, this study evaluates the impacts of the investor-base effect and the information effect of investor attention on market correction following extreme daily returns in the US stock market from 1966 to 2018.FindingsThis study finds that the investor-base effect increases subsequent returns of both daily winner and daily loser stocks. The information effect leads to economically less significant return reversals for both the daily winner and daily loser stocks. These two effects tend to have economically more significant impacts on the daily loser stocks. The economic significance of these two effects is also related to firm size and the state of the stock market.Originality/valueThis study is the first to disentangle the investor-base effect and the information effect of increased investor attention. The evidence that the information effect facilitates the dissemination of new information and impacts stock returns contributes to the strand of studies on the impact of investor attention on market efficiency. This evidence also contributes to the strand of studies analyzing the impact of informational trading on stock returns. In addition, this study provides evidence for market overreaction and the subsequent correction. The results for up and down markets contribute to the literature on the investors' trading behavior.

scholarly journals COVID-19 fear index: does it matter for stock market returns?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sowmya Subramaniam ◽  
Madhumita Chakraborty
Keyword(s):  
Stock Market ◽  
Volume Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Significant Period ◽  
Search Terms ◽  
Search Volume ◽  
Fear Index ◽  
Google Search

PurposeThe purpose of this paper is to capture the investors' mood related to the COVID-19 pandemic and analyze its impact on the stock market returns.Design/methodology/approachTo capture the investor mood related to the COVID-19 pandemic, the authors construct a unique COVID-19 fear index based on the Search Volume Index (SVI) from Google Trends (http://www.Google.com/trends/) of the search terms related to COVID-19 words and phrases as revealed by Google and Internet dictionaries. The COVID-19 fear index was used to investigate its impact on the stock market returns.FindingsThe study finds a strong negative association between COVID-19 fear and stock returns. Unlike other studies, the relationship is persistent for a significant period. This relationship is not found to reverse in the following days. The results also highlight that COVID-19 fear strongly impacts the stock market. The sentiment persists for a significant period and is not reversed soon, unlike the regular times in earlier studies.Originality/valueThe study is among the very few studies that constructed COVID-19 fear index using several Google search terms and captured its impact on the stock market returns.

scholarly journals Stock market activity and Google Trends: the case of a developing economy

2019 ◽  
Vol 21 (2) ◽  
pp. 191-212
Author(s):  
Vinh Xuan Bui ◽  
Hang Thu Nguyen
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Design Methodology ◽  
Investor Attention ◽  
Content Type ◽  
Market Activity ◽  
Search Terms ◽  
Search Volume ◽  
Stock Indices ◽  
Google Search

Purpose The purpose of this paper is to investigate the impacts of investor attention on stock market activity. Design/methodology/approach The authors employed the Google Search Volume (GSV) Index, a direct and non-traditional proxy for investor attention. Findings The results indicate a strong correlation between GSV and trading volume – a traditional measure of attention – proving the new measure’s reliability. In addition, market-wide attention increases both stock illiquidity and volatility, whereas company-level attention shows mixed results, driving illiquidity and volatility in both directions. Originality/value To the best of the authors’ knowledge, Nguyen and Pham’s (2018) study has been the only previous study identifying investor attention in Vietnam by using GSV as a proxy and examining the impacts of broad search terms about the macroeconomy on the stock market as a whole – on stock indices’ movements. The paper will contribute to this by quantifying GSV impacts on each stock individually.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

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.

COVID-19 pandemic sentiment and stock market behavior: evidence from an emerging market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Byomakesh Debata ◽  
Kshitish Ghate ◽  
Jayashree Renganathan
Keyword(s):  
Stock Market ◽  
Emerging Market ◽  
Sample Period ◽  
Market Behavior ◽  
Market Returns ◽  
Full Sample ◽  
Content Type ◽  
Time Frequency ◽  
Search Volume ◽  
Google Search

PurposeThis study aims to examine the relationship between pandemic sentiment (PS) and stock market returns in an emerging order-driven stock market like India.Design/methodology/approachThis study uses nonlinear causality and wavelet coherence techniques to analyze the sentiment-returns nexus. The analysis is conducted on the full sample period from January to December 2020 and further extended to two subperiods from January to June and July to December to investigate whether the associations between sentiment and market returns persist even several months after the outbreak.FindingsThis study constructs two novel measures of PS: one using Google Search Volume Intensity and the other using Textual Analysis of newspaper headlines. The empirical findings suggest a high degree of interrelationship between PS and stock returns in all time-frequency domains across the full sample period. This interrelationship is found to be further heightened during the initial months of the crisis but reduces significantly during the later months. This could be because a considerable amount of uncertainty regarding the crisis is already accounted for and priced into the markets in the initial months.Originality/valueThe ongoing coronavirus pandemic has resulted in sharp volatility and frequent crashes in the global equity indices. This study is an endeavor to shed light on the ongoing debate on the COVID-19 pandemic, investors’ sentiment and stock market behavior.

scholarly journals Google Search and Stock Market Performance: Evidence from Malaysia

2019 ◽  
Vol 2 (1) ◽  
pp. 49-55
Author(s):  
Kelvin Yong Ming Lee
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Trading Volume ◽  
Market Performance ◽  
Volume Index ◽  
Investment Strategies ◽  
Search Volume ◽  
Stock Market Performance ◽  
Google Search ◽  
The Relationship

Nowadays, the internet changes the way for information searching and processing. Along with that, Google search had become the most popular search engine on the web since it allows users access to the information at a minimal cost. This study intends to investigate the relationship between Google search volume and the Malaysian stock market performance in the aspects of returns, volatility, and trading volume. The sample of this study consisted of 29 listed companies from the Malaysian stock market. The sample period of this study covered the period from 2016 to 2018. The data related to the stock market were downloaded from Investing.com, whereas the data related to Google search were downloaded from the database of Google Trend. The results indicated that the Google search volume index (GSVI) of the previous week tends to have significant positive impacts on the stock price changes. Thus, a higher search volume of the specific company name tends to increase the stock price of the particular company in the following week. Besides that, this study also revealed that the stock market performance tends to be affected by stock market performance in the previous week. Lastly, this study suggested that signals of GSVI need to be included in the investment strategies.  

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