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.

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 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.

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.  

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.

Herd behavior in the French stock market

2017 ◽  
Vol 16 (4) ◽  
pp. 497-515 ◽  
Author(s):  
Houda Litimi
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Design Methodology ◽  
Garch Model ◽  
Herd Behavior ◽  
Conditional Volatility ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type

Purpose This paper aims to investigate the herding behavior in the French stock market and its effect on the idiosyncratic conditional volatility at a sectoral level. Design/methodology/approach This sample covers all the listed companies in the French stock market, classified by sector, over four major crisis periods. The author modifies the cross-sectional absolute deviation (CSAD) model to include trading volume and investors sentiment as herding triggers. Furthermore, the author uses a modified GARCH model to investigate the effect of herding on conditional volatility. Findings Herding is present in the French market during crises, and it is present in only some sectors during the entire period. The main trigger for investors to embark into a collective herding movement differs from one sector to another. Furthermore, herding behavior has an inhibiting effect on market conditional volatility. Originality/value The author modifies the CSAD model to investigate the presence of herding in the French stock market at a sectoral level during turmoil periods. Furthermore, the particularly designed GARCH model provides new insights on the effect of herding and volume turnover on the conditional volatility.

scholarly journals Investors’ attention: does it impact the Nigerian stock market activities?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Osarumwense Osabuohien-Irabor
Keyword(s):  
Stock Market ◽  
Regression Model ◽  
Stock Markets ◽  
Trading Volume ◽  
Stock Return ◽  
Search Query ◽  
Content Type ◽  
Page View ◽  
Information Demand ◽  
Google Search

PurposeThe author investigates whether investors’ online information demand measured by Google search query and the changes in the numbers of Wikipedia page view can explain and predict stock return, trading volume and volatility dynamics of companies listed on the Nigerian Stock Exchange.Design/methodology/approachThe multiple regression model which encompasses both the univariate and multivariate regression framework was employed as the research methodology. As part of our pre-analysis, we test for multicollinearity and applied the Wu/Hausman specification test to detect whether endogeneity exist in the regression model.FindingsWe provide novel and robust evidence that Google searches neither explain the contemporaneous nor predict stock return, trading volume and volatility dynamics. Similarly, results also indicate that trading volume and volatility dynamics have no relationship with changes in the numbers of Wikipedia pages view related to stock activities.Originality/valueThis study opens new strand of empirical literature of “investors' attention” in the context of African stock markets as empirical evidence. No evidence from previous studies on investors' attention exist, whether in Google search query or Wikipedia page view, with respect to African stock markets, particularly the Nigerian stock market. This study seeks to bridge these knowledge gaps by examining these relations.

scholarly journals Investor Attention and Stock Market Activities: New Evidence from Panel Data

2019 ◽  
Vol 7 (2) ◽  
pp. 30 ◽  
Author(s):  
Chaiyuth Padungsaksawasdi ◽  
Sirimon Treepongkaruna ◽  
Robert Brooks
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Investor Attention ◽  
Developed Markets ◽  
Search Volume ◽  
Developing Markets ◽  
Prior Literature ◽  
Panel Vector Autoregression ◽  
New Evidence

Using the panel vector autoregression (VAR) method, this paper documents relationships between investor attention and stock market activities; i.e., return, volatility, and trading volume, respectively. In sum, bidirectional dynamic interdependence of the SVI–stock market activities relationship exists, in which the SVI–trading volume relationship shows the strongest evidence. This is consistent with prior literature using trading volume as a proxy of investor attention. However, the relationships in the developed and developing markets are statistically significantly different. The stock markets in the developed markets over-react more to the search volume than those in the developing markets. We postulate that investor attention is one of the key elements in asset pricing in stock markets.

scholarly journals Islamic equities and COVID-19 pandemic: measuring Islamic stock indices correlation and volatility in period of crisis

2021 ◽  
Vol 29 (1) ◽  
pp. 50-66
Author(s):  
Shafiu Ibrahim Abdullahi
Keyword(s):  
Stock Market ◽  
Generalized Method Of Moments ◽  
Multivariate Garch ◽  
Content Type ◽  
Volatility Transmission ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Stock Indices ◽  
Cointegration Tests ◽  
Normal Correlation

PurposeThe purpose of the study is to measure cross-country stock market correlation and volatility transmission during the global coronavirus disease 2019 (COVID-19) pandemic. The paper traces trajectory of Islamic equity investments in order to get insights on the behavior of the markets during the crisis.Design/methodology/approachThe paper uses generalized method of moments (GMM), autoregressive distributed lag (ARDL) and multivariate GARCH (MGARCH) models for analysis of dynamic causality, stock market cointegration, correlation and volatility transmission between Islamic stock indices.FindingsThe result of normal correlation analysis on the share indices show the markets move together. The result of ARDL cointegration test shows the markets returns are cointegrated as a group. To further make sense of the data; the indices were grouped into four different categories, then cointegration tests were conducted. The results of the analysis show that the subgroups are cointegrated except the low COVID-19 subgroup. Based on MGARCH findings, the possibility of volatility transmission between markets during the crisis is high. The market returns indices show the usual herd mentality common during the period of crisis.Originality/valueUnlike other works in this area, this paper attempt to trace the trajectory of Islamic equity investment in order to get relevant insights and arrives at appropriate ways of responding to the crisis.

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