scholarly journals The Influence of Google Search Intensity on the Stability of the Indonesian Capital Market in the Perspective of the Defense Economy

2021 ◽  
Vol 04 (11) ◽  
Author(s):  
Darnis Darnis ◽  
Keyword(s):  
Capital Market ◽  
Trading Volume ◽  
Banking Sector ◽  
Sampling Technique ◽  
Volume Index ◽  
Search Intensity ◽  
Search Volume ◽  
Abnormal Trading Volume ◽  
The Stability ◽  
Google Search

This study aims to determine the Influence of Google Search Intensity on the Stability of the Indonesian Capital Market, as well as looking at the defense and security aspects, especially the economy. The research sample is the shares of the banking sector companies listed on the Indonesia Stock Exchange for the 2016-2018 period. The independent variable used in this study is the Abnormal Search Volume Index. The control variables used are Volatility, and Abnormal Trading Volume Lagged. The dependent variable used is Abnormal Trading Volume. The sampling method used in this study used a purposive sampling technique. Obtained the number of samples as many as 18 companies. The analysis technique used in this research is panel data regression. The results of this study indicate that the intensity of Google searches using the ASVI proxy has a significant positive effect on the stability of the stock represented by Abnormal Trading Volume. This illustrates that the use of Google search intensity data can be used as a reference in making defense policies against non-military threats, especially the stability of the Indonesian Capital Market.

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.

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.

Pengaruh Laba Bersih, Arus Kas Dan Dividen Tunai Terhadap Volume Perdagangan Saham Pada Perusahaan Publik Sektor Barang Dan Konsumsi Di BEI

2019 ◽  
Vol 4 (1) ◽  
pp. 32
Author(s):  
Etty Susilowati ◽  
Hernawati Sinaga
Keyword(s):  
Cash Flow ◽  
Capital Market ◽  
Trading Volume ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Net Income ◽  
Stock Trading ◽  
Public Companies ◽  
Positive Effects ◽  
The Capital Market

The stock trading volume is the number of shares that are traded on the capital market every trading day with a price level agreed upon by the seller and buyer through an intermediary in the capital market. Stocks will be more liquid with the amount of investment in shares. To assess the volume of stock trading, investors can evaluate net income, cash flow and cash dividends. The purpose of this study was to analyze the effect of net income, cash flow and cash dividends on the volume of stock trading in 10 public goods and consumption sectors listed on the Indonesia Stock Exchange (IDX) through a purposive sampling technique both simultaneously and partially. The research data were analyzed using multiple linear regression methods. The results of this study indicate that simultaneously net income, cash flow and cash dividends have significant effects on the volume of stock trading of public companies in the goods and consumption sector, while partially, only net income (β = 0.485) and cash flow (β= 1.587) have significant positive effects against the volume of stock trading.

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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