Identification of information networks in stock markets

Baltakienė, Margarita; Kanniainen, Juho; Baltakys, Kęstutis

doi:10.1016/j.jedc.2021.104217

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…They concluded that there is the significant volatility spillover in five BRIICS economies except for Brazil. In addition, a few scholars focus on the complex network to identify the financial risk spillover and financial risk (Baltakien et al, 2021; Wen et al, 2021). Chen, Wen, et al (2022) applied complex network to study the volatility among Chinese mainland stock markets and Hong Kong stock market, they found that the mainland stock markets are always obvious net senders of spillover.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk spillover networks in financial markets: Evidence from emerging markets

Jin

Liu

2023

Manage Decis Econ

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This paper empirically explores dynamic risk impact of extreme volatility between stock and foreign exchange markets in emerging markets. Based on CoVaR analysis, we construct networks to investigate the nonlinear and dynamic evolution characteristics of risk contagion. The results show that stock and foreign exchange markets exhibit asymmetric tail dependence. All networks present small world network characteristics. The risk tolerance impact is more noticeable than risk overflow and stock markets are more sensitive to risk contagion. In the minimum spanning tree (MST), Korean stock market and foreign exchange markets of India and China are critical nodes in the minimum path of risk overflow.

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Section: Literature Reviewmentioning

confidence: 99%

Risk spillover networks in financial markets: Evidence from emerging markets

Jin

Liu

2023

Manage Decis Econ

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“…Social media have become a source of opinion formation, adding emotions and creating fake information that affects important decisions in financial markets (NASDAQ 2019). In fact, there are formal and informal channels of information in the financial market, and investors' use of information sources is often determined by their co-existence (Baltakien ė et al 2021). Given the advantages and disadvantages of various sources of information for investment decision making, it is important to investigate how investors prioritize sources of information.…”

Section: Introductionmentioning

confidence: 99%

Information Sources for Investment Decisions: Evidence from Japanese Investors

Lal,

Sulemana,

Nguyen

et al. 2023

IJFS

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Although the traditional sources of financial knowledge in Japan are financial advisors and investment groups, the digital era and artificial intelligence have made other sources of information, such as social media and mass media, more influential. As such, it has become important to examine the socioeconomic, demographic, and psychological factors influencing the use of these information sources in the context of investment decisions. However, little research has been carried out to examine such associations using a large-scale nationwide dataset. We fill this gap by utilizing a dataset comprising almost 65,000 active investors from one of the largest online security companies in Japan, ensuring the representativeness and generalizability of our results. We show that active investors are more inclined to use social media and mass media than financial advisors and investment groups. The probit regression model shows that the use of each of the four sources of information is strongly shaped by an individual’s characteristics, which, to some extent, are not mutually exclusive for each source type. The study results imply that the government should regulate and monitor the quality and accuracy of the information disseminated by mass media and social media and educate investors on how to critically evaluate and verify the information that they receive.

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