Social Media, Internet Sentiment Tracking and Stock Market Volatility

2022 ◽  
Vol 20 (1) ◽  
pp. 1
Author(s):  
Yu Ting Mai ◽  
Yi Hsien Wang ◽  
Kuang Hsun Shih ◽  
Fu Ju Yang
2019 ◽  
Vol 15 (5) ◽  
pp. 510-534
Author(s):  
Jie She ◽  
Tao Zhang

Purpose This study aims to investigate whether and to what extent the characteristics of headlines impact the attraction of online financial articles by using data collected from WeChat, a popular social app in China. Design/methodology/approach By integrating the methods of econometric and text mining, this study analyzed the content of 113,917 headlines published by 126 official accounts from the day account being created to May 12, 2016. Hierarchical regression was used to investigate the effects of headline features, account ownership type and stock market volatility on the attraction of online financial articles. Findings The empirical results show that sentiment, length, domain specificity and language intensity in a headline are significantly associated with the attraction of an online financial article. In addition, the relative and moderating roles of stock market volatility and account ownership type were also explored, showing significant moderating effects on the relationship between sentiment and online article attraction. Research limitations/implications This study had several limitations. First, the sample data for this research were collected from one social media platform. While WeChat is the most popular social media application in China, it is just one of the many social media applications that can be used to publish online financial articles, and it differs from other social media applications greatly. This makes it hard to generalize the conclusions of the study. Future studies could compare the different features of headlines and their effects on the attraction of financial articles on different platforms. Second, in mining the characteristics of headline, this study only analyzed the influence of the sentiment, domain specificity, length and language intensity of the headline on article attraction. In future studies, in-depth analysis of the headline content could be conducted, such as the similarity between the body text and the headline, the theme and the sense of humor. However, the authors believe that these limitations do not have major negative implications for the results and contributions of this study. Practical implications From a practical perspective, this work could help official WeChat accounts to write better headlines for the articles they publish to attract more readers and fans and thus improve the value of their accounts, which would enable them to maximize the tangible benefits through differential pricing on advertisement placement. Originality/value The contributions of this study are as follows. First, the paper explored how headline sentiment influences article attraction and found that positive sentiment is negatively related to article attraction, while negative sentiment is positively related to article attraction. In addition, there is an inverted U-shaped relationship between the extent of negative sentiment and article attraction. Second, the paper investigates how headline domain specificity affects article attraction and there is an inverted U-shaped relationship between headline domain specificity and article attraction. Third, to the best of the authors’ knowledge, this is the first large-scale case study that explores the association between stock market volatility and the attraction of an online financial article.


Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1212
Author(s):  
Pierdomenico Duttilo ◽  
Stefano Antonio Gattone ◽  
Tonio Di Di Battista

Volatility is the most widespread measure of risk. Volatility modeling allows investors to capture potential losses and investment opportunities. This work aims to examine the impact of the two waves of COVID-19 infections on the return and volatility of the stock market indices of the euro area countries. The study also focuses on other important aspects such as time-varying risk premium and leverage effect. This investigation employed the Threshold GARCH(1,1)-in-Mean model with exogenous dummy variables. Daily returns of the euro area stock markets indices from 4th January 2016 to 31st December 2020 has been used for the analysis. The results reveal that euro area stock markets respond differently to the COVID-19 pandemic. Specifically, the first wave of COVID-19 infections had a notable impact on stock market volatility of euro area countries with middle-large financial centres while the second wave had a significant impact only on stock market volatility of Belgium.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Faheem Aslam ◽  
Hyoung-Goo Kang ◽  
Khurrum Shahzad Mughal ◽  
Tahir Mumtaz Awan ◽  
Yasir Tariq Mohmand

AbstractTerrorism in Pakistan poses a significant risk towards the lives of people by violent destruction and physical damage. In addition to human loss, such catastrophic activities also affect the financial markets. The purpose of this study is to examine the impact of terrorism on the volatility of the Pakistan stock market. The financial impact of 339 terrorist attacks for a period of 18 years (2000–2018) is estimated w.r.t. target type, days of the week, and surprise factor. Three important macroeconomic variables namely exchange rate, gold, and oil were also considered. The findings of the EGARCH (1, 1) model revealed that the terrorist attacks targeting the security forces and commercial facilities significantly increased the stock market volatility. The significant impact of terrorist attacks on Monday, Tuesday, and Thursday confirms the overreaction of investors to terrorist news. Furthermore, the results confirmed the negative linkage between the surprise factor and stock market returns. The findings of this study have significant implications for investors and policymakers.


2021 ◽  
pp. 097226292199098
Author(s):  
Vaibhav Aggarwal ◽  
Adesh Doifode ◽  
Mrityunjay Kumar Tiwary

This study examines the relationship that both domestic and foreign institutional net equity flows have with the India stock markets. The motivation behind is the study to examine whether increased net equity investments from domestic institutional investors has reduced the influence of foreign equity flows on the Indian stock market volatility. Our results indicate that only during periods in which domestic equity inflows surpass foreign flows by a significant margin, as seen during 2015–2018, is the Indian stock market volatility not significantly influenced by foreign equity investments. However, during periods of re-emergence of strong foreign net inflows, the Indian market volatility is still being impacted significantly, as has been observed since 2019. Furthermore, we find that both large-scale net buying and net selling by domestic funds increased the stock market volatility as observed during 2015–2018 and COVID-impacted year 2020 respectively. The implications of this study are multi-fold. First, the regulators should discuss with industry bodies before enforcing major structural changes like reconstituting of mutual fund investment mandate in 2017 which forced domestic funds to quickly change portfolio allocation amongst large-cap, mid-cap and small-cap stocks resulting in higher stock market volatility. Second, adequate investor educational and awareness programmes need to be conducted regularly for retail investors to minimize herd behaviour of investing during market rise and heavy redemptions at times of fall. Third, the economic policies should be stable and forward-looking to ensure foreign investors remain attracted to the Indian stock markets at all times.


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