Transmission effect of extreme risks in China's financial sectors at major emergencies: Empirical study based on the GPD-CAViaR and TVP-SV-VAR approach

Mo, Tingcheng; Xie, Chi; Li, Kelong; Ouyang, Yingbo; Zeng, Zhijian

doi:10.3934/era.2022236

Cited by 4 publications

(1 citation statement)

References 32 publications

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“…Other scholars have investigated the impact of major emergencies, such as Ukwuoma [5], Benifa [6], Asif [7], and Fazmiya [8], who analyzed the physical effects of major emergencies on humans from a medical perspective, using COVID-19 as an example. Mo et al [9] argued that major emergencies have both an emotional as impact as well as a huge economic impact. Cheng et al [10] found that secondary disasters of major emergencies can have an impact on international oil prices.…”

Section: Related Workmentioning

confidence: 99%

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Li,

Sun

et al. 2024

Front. Phys.

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In order to effectively prevent and combat online public opinion crises triggered by major emergencies, this paper explores the dissemination mechanism of uncertain information on online social platforms. According to the decision-making behavior of netizens after receiving uncertain information, they are divided into eight categories. Considering that there will be a portion of netizens who clarify uncertain information after receiving it, this paper proposes a SEFTFbTbMR model of uncertain information clarification behavior. The propagation dynamics equations of the model are given based on the theory of differential equations, the basic regeneration number R0 of the model is calculated, and the existence and stability of the equilibrium point of the model are analyzed. The theoretical analysis of the model is validated using numerical simulation software, and sensitivity analysis is performed on the parameters related to R0. In order to reduce the influence caused by uncertain information, the optimal control strategy of the model is proposed using the Hamiltonian function. It is found that the dissemination of uncertain information among netizens can be suppressed by strengthening the regulation of social platforms, improving netizens’ awareness of identifying the authenticity of information, and encouraging netizens to participate in the clarification of uncertain information. The results of this work can provide a theoretical basis for future research on the uncertain information dissemination mechanism triggered by major emergencies. In addition, the results can also provide methodological support for the relevant government departments to reduce the adverse effects caused by uncertain information in the future.

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Section: Related Workmentioning

confidence: 99%

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Li,

Sun

et al. 2024

Front. Phys.

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Dynamic evolutionary analysis of opinion leaders’ and netizens’ uncertain information dissemination behavior considering random interference

Ma,

Li,

Wang

2024

Front. Phys.

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This paper investigates the decision-making behaviors of opinion leaders and netizens in the context of uncertain information dissemination with the aim of effectively managing online public opinion crises triggered by major sudden events. The decision-making behaviors of opinion leaders are categorized into positive and negative guidance, while those of netizens are classified into acceptance and nonacceptance. Using an evolutionary game model, this study introduces random factors to examine their influence on the decision-making processes of both groups. A stochastic evolutionary game model is constructed to analyze the behaviors of opinion leaders and netizens in the context of uncertain information dissemination. The evolutionary stability strategies and stochastic evolutionary processes of the model are analyzed based on the theory of Itô stochastic differential equations. The impacts of key variables such as random disturbances, the degree of psychological identification of netizens with opinion leaders, and the intensity of government penalties for those spreading negative information are examined through numerical simulations. The findings indicate that opinion leaders evolve to make stable strategies more rapidly than netizens do; random disturbances slow the evolution of stable strategies for both groups but do not alter their strategic choices; a higher degree of psychological identification increases the likelihood of netizens adopting the views of opinion leaders; and as punitive measures intensify, both opinion leaders and netizens are inclined to choose strategies of positive guidance and acceptance. The results of this study offer theoretical insights and decision-making guidance for future government strategies for managing similar online collective behaviors.

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Systemic risk prediction based on Savitzky-Golay smoothing and temporal convolutional networks

Yang

Zou

Cao

et al. 2023

era

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<abstract><p>Based on the data from January 2007 to December 2021, this paper selects 14 representatives from four levels of the extreme risk of financial institutions, the contagion effect between financial systems, volatility and instability of financial markets, liquidity, and credit risk systemic risk. By constructing a Savitzky-Golay-TCN deep convolutional neural network, the systemic risk indicators of China's financial market are predicted, and their accuracy and reliability are analyzed. The research found that: 1) Savitzky-Golay-TCN deep convolutional neural network has a strong generalization ability, and the prediction effect on all indices is stable. 2) Compared with the three control models (time-series convolutional network (TCN), convolutional neural network (CNN), and long short-term memory (LSTM)), the Savitzky-Golay-TCN deep convolutional neural network has excellent prediction accuracy, and its average prediction accuracy for all indices has increased. 3) Savitzky-Golay-TCN deep convolutional neural network can better monitor financial market changes and effectively predict systemic risk.</p></abstract>

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Transmission effect of extreme risks in China's financial sectors at major emergencies: Empirical study based on the GPD-CAViaR and TVP-SV-VAR approach

Cited by 4 publications

References 32 publications

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Dynamics analysis and optimal control study of uncertain information dissemination model triggered after major emergencies

Dynamic evolutionary analysis of opinion leaders’ and netizens’ uncertain information dissemination behavior considering random interference

Systemic risk prediction based on Savitzky-Golay smoothing and temporal convolutional networks

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