scholarly journals Investor Attention and Corporate Innovation Performance: Evidence from Web Search Volume Index of Chinese Listed Companies

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 930
Author(s):  
Nian Li ◽  
Chunling Li ◽  
Runsen Yuan ◽  
Muhammad Asif Khan ◽  
Xiaoran Sun ◽  
...  
Keyword(s):  
Economic Development ◽  
Information Asymmetry ◽  
Listed Companies ◽  
Agency Cost ◽  
Innovation Performance ◽  
Volume Index ◽  
Investor Attention ◽  
Search Volume ◽  
Corporate Innovation ◽  
Chinese Listed Companies

Leveraging from the online search index of Chinese listed companies from 2012 to 2018, we empirically test the relationship between investors’ attention and corporate innovation performance for the first time. The main results are as follows: (1) investors’ attention significantly improves listed companies’ innovation performance, which is reflected in the increase of patent applications. This indicates that investors’ active information collection behaviour affects China’s economic development by promoting enterprise innovation. (2) This paper’s conclusion remains intact after a battery of robustness checks, such as alternative measures of key variables and empirical specifications and a series of endogenous treatment. (3) The mechanisms tests show that: “information asymmetry”, “financing constraint”, and “agency cost” are supported. In other words, with the increase of investors’ attention, not only the information asymmetry is reduced, which greatly improved the information environment of the capital market, but also the external financing constraints of enterprises are alleviated. The opportunistic management behaviour is effectively suppressed, thus motivating the corporate innovation incentives and improving the corporate innovation of input, output and quality. (4) Further research shows that investor attention to listed companies also improves the efficiency of capital allocation. This paper’s conclusion shows that investors’ initiative information acquisition behaviour can improve enterprises innovation performance, thus providing a driving force for China’s economic development.

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.

scholarly journals Customer Concentration and Corporate Innovation: Effects of Financing Constraints and Managers’ Expectation of Chinese Listed Companies

2019 ◽  
Vol 11 (10) ◽  
pp. 2859 ◽  
Author(s):  
Bing Zhou ◽  
Yumeng Li ◽  
Shengzhong Huang ◽  
Sidai Guo ◽  
Bing Xue
Keyword(s):  
Fixed Effects ◽  
Threshold Model ◽  
Threshold Effect ◽  
Listed Companies ◽  
Financing Constraints ◽  
Innovation Capability ◽  
Corporate Innovation ◽  
Chinese Listed Companies ◽  
The Relationship ◽  
Double Threshold

Innovation capability of enterprises will greatly influence the current and future development of companies. This paper investigates the relationship between customer concentration and innovation capability of enterprises through the view of both the financing constraints and the expectation of managers. Based on the data of China’s A-share listed companies over the period from 2012 to 2016, several methods including system GMM, threshold model of fixed effects, and PSM are applied for empirical analysis. The results show that the innovation capability of listed companies in China are negatively correlated with the customer concentration. Higher customer concentration brings about stronger constraints from large customers on enterprises and greater dependence of enterprises on large customers, which result in weaker demand for innovation and lower investment in innovation. Meanwhile, the results demonstrate the double-threshold effect of financing constraints. The effect of customer concentration on innovation can be different in companies with low, medium, or high-financing constraints. Furthermore, optimistic expectations are more conducive to the reduction of customer concentration and the improvement of innovation. In addition, based on the perspective of the manager’s expectation, the research demonstrates the heterogeneous impact of manager’s expectation on the relationship between customer concentration and innovation capability.

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.

The research on the relationship between corporate innovation, enforcement and board characteristics on the background of artificial intelligence–taking chinese listed companies as an example

2021 ◽  
Vol 40 (4) ◽  
pp. 8587-8599
Author(s):  
Wang Rui ◽  
Gu Qiuyang ◽  
Yang Zhijiao
Keyword(s):  
Artificial Intelligence ◽  
Listed Companies ◽  
Research Literature ◽  
Stock Exchanges ◽  
Moderator Effect ◽  
Board Characteristics ◽  
Corporate Innovation ◽  
Chinese Listed Companies ◽  
Innovation Ability ◽  
The Relationship

In this era of artificial intelligence and information, the transformation and upgrading of enterprises plays a crucial role in their development. This study analyzes the regulatory penalties of listed companies published by the Shenzhen and Shanghai stock exchanges from 1996 to 2017, and explores the relationship between the number of enforcements of these companies and their innovation ability. Existing research literature confirms that board characteristics, including the gender of the CEO and whether the CEO has an overseas background, will have a significant impact on the company’s ability to innovate and the likelihood of corporate penalties. Therefore, this study selects the two moderator variables of the chairman’s gender and whether the chairman has overseas study background. This study uses the To bit model and establishes three hypotheses to verify whether the company’s ability to innovate can significantly affect the number of times they are enforced, whether the chairman’s gender and whether the chairman’s overseas background will have a moderator effect on this relationship. The analysis results confirm these three assumptions.

scholarly journals Investors’ Attention and Its Effect on Saudi Stock Returns

2020 ◽  
Vol 15 ◽  
pp. 26-34
Author(s):  
Hesah Hesah Aljarbou
Keyword(s):  
Decision Making ◽  
Stock Returns ◽  
Volume Index ◽  
Process Information ◽  
Investor Attention ◽  
Amount Of Information ◽  
Search Volume ◽  
The Individual

The study examines the individual investor's intention effect of attention-grabbing stocks such as stocks in the news, stock experiencing high abnormal trading, and stocks with high returns. Attention driven trading results from an individual investor's ability to process information when being exposed to a large amount of information. The study includes Google’s Search Volume Index (SVI) as a proxy for investor attention. Thus, preferences of certain stocks determine decision making after attention has determined the selected stock in which trading is increased. 

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