scholarly journals Measurement of Investor Sentiment and Its Bi-Directional Contemporaneous and Lead–Lag Relationship with Returns: Evidence from Pakistan

2018 ◽  
Vol 11 (1) ◽  
pp. 94 ◽  
Author(s):  
Mehwish Khan ◽  
Eatzaz Ahmad
Keyword(s):  
Emerging Market ◽  
Investor Sentiment ◽  
Volume Index ◽  
Sufficient Evidence ◽  
Market Returns ◽  
Search Volume ◽  
Irrational Behavior ◽  
Thin Market ◽  
Google Search

The present study examines bi-directional contemporaneous and lead–lag relationships between investor sentiment and market returns in the emerging market of Pakistan over the period of 2006 to 2016. To measure investor sentiment, the study employs a direct proxy namely Google search volume index (GSVI) and nine other indirect proxies. Besides conventional regression and VAR model, the study applies Geweke’s (1982) tests to investigate the nature of relationships between sentiment and returns. Thus, the study adds to existing literature by providing latest and thorough statistical evidence on the role of investor sentiment in influencing market returns. The study finds sufficient evidence regarding irrational behavior of investors in the thin market of Pakistan. In particular, the results indicate substantive role of sentiment in dragging stock market away from its sustainable path as implied by economic fundamentals.

Googling Investor Sentiment around the World

2019 ◽  
Vol 55 (2) ◽  
pp. 549-580 ◽  
Author(s):  
Zhenyu Gao ◽  
Haohan Ren ◽  
Bohui Zhang
Keyword(s):  
Stock Prices ◽  
Stock Markets ◽  
Investor Sentiment ◽  
Search Behavior ◽  
Market Returns ◽  
Country Level ◽  
The World ◽  
Google Search

We study how investor sentiment affects stock prices around the world. Relying on households’ Google search behavior, we construct a weekly measure of sentiment for 38 countries during 2004–2014. We validate the sentiment index in tests using sports outcomes and show that the sentiment measure is a contrarian predictor of country-level market returns. Furthermore, we document an important role of global sentiment in stock markets.

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 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.

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.

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.

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