Simulation of financial risk spillover effect based on ARMA-GARCH and fuzzy calculation model

2020 ◽  
pp. 1-12
Author(s):  
Chong Wang ◽  
Yuesong Wei
Keyword(s):  
Financial Development ◽  
Financial Risk ◽  
Financial Analysis ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Calculation Model ◽  
Multiple Risk Factors ◽  
Effect Model ◽  
Risk Spillover Effects ◽  
Case Data

Convergence and spillover are the characteristics shown in the process of financial development. By verifying whether there is convergence and spillover in financial development within a certain region and between regions, the stage of financial development in the region can be more accurately judged. This paper combines the actual needs of financial analysis to construct a financial risk spillover effect model based on ARMA-GARCH and fuzzy calculation. The model uses ARMA-GARCH and fuzzy algorithm to verify the financial multiple risk factors. Moreover, in order to verify the effect of the model, this paper uses case data analysis to study the model effect and combines mathematical statistics to process the model data. The research results show that the model constructed in this paper has a certain effect, and the ARMA-GARCH model is suitable for analysis and research on financial risk spillover effects. At the same time, when the statistical distribution is used to fit its error distribution, the fitting and prediction effect of the model is better.

Analysis of risk spillover effect of copper option in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wuyi Ye ◽  
Yiqi Wang ◽  
Jinhai Zhao
Keyword(s):  
Value At Risk ◽  
Risk Model ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Futures Market ◽  
Content Type ◽  
Conditional Autoregressive ◽  
Derivative Markets ◽  
The Impact ◽  
Risk Spillover Effects

Purpose The purpose of this paper is to compare the changes in the risk spillover effects between the copper spot and futures markets before and after the issuance of copper options, analyze the risk spillover effects between the three markets after the issuance of the options and can provide effective suggestions for regulators and investors who hedge risks. Design/methodology/approach The MV-CAViaR model is an extended form of the vector autoregressive model (VAR) to the quantile model, and it is also a special form of the MVMQ-CAViaR model. Based on the VAR quantile model, this model has undergone continuous promotion of the Conditional Autoregressive Value-at-Risk Model (CAViaR) and the Multi-quantile Conditional Autoregressive Value-at-Risk Model (MQ-CAViaR), and finally got the current form of the model. Findings The issuance of options has led to certain changes in the risk spillover effect between the copper spot and its derivative markets, and the risk aggregation effect in the futures market has always been significant. Therefore, when supervising the copper product market and investors using copper derivatives to avoid market risks, they need to pay attention to the impact of futures on the spot market, the impact of options on the futures market and the risk spillover effects of spot and futures on the options market. Practical implications The empirical results of this paper can be used to hedge market risk investment strategies, and the changes in market relationships also provide an effective basis for the supervision of the copper product market by the supervisory authority. Originality/value It is the first literature research to discuss the risk and the impact of spillover effects of copper options on China copper market and its derivative markets. The MV-CAViaR model can capture the mutual risk influence between markets by modeling multiple markets simultaneously.

Risk spillover in financial markets based on support vector quantile regression

2020 ◽  
pp. 1-11
Author(s):  
Wangsong Xie
Keyword(s):  
Quantile Regression ◽  
Financial Markets ◽  
Financial Market ◽  
Financial Risk ◽  
Spillover Effects ◽  
Market Risk ◽  
Support Vector ◽  
Non Linear ◽  
Risk Spillover Effects ◽  
Financial Market Risk

In terms of financial market risk research, with the rapid popularization of non-linear perspectives and the improvement of theoretical reasoning, scholars have slowly broken through the cage of linear ideas and derived new and more practical methods from non-linear perspectives to make up for the shortcomings of traditional research. Based on the support vector classification regression algorithm, this research combines the typical facts and characteristics of financial markets, from the perspective of quantile regression and SVR intelligent technology in computer science, to explore the research method of financial market risk spillover effects from a nonlinear perspective. Moreover, this research integrates statistical research, machine learning and other related research methods, and applies them to the measurement of financial risk spillover effects. The empirical analysis shows that the method proposed in this paper has certain effects, and financial risk analysis can be performed based on the risk spillover effect measurement model constructed in this paper.

scholarly journals Asymmetric Risk Spillover Networks and Risk Contagion Driver in Chinese Financial Markets: The Perspective of Economic Policy Uncertainty

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zongxin Zhang ◽  
Ying Chen ◽  
Weijie Hou
Keyword(s):  
Economic Policy ◽  
Real Estate ◽  
Financial Markets ◽  
Financial Risk ◽  
Positive Impact ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
The Impact

The global financial market shocks have intensified due to the COVID-19 epidemic and other impacts, and the impacts of economic policy uncertainty on the financial system cannot be ignored. In this paper, we construct asymmetric risk spillover networks of Chinese financial markets based on five sectors: bank, securities, insurance, diversified finance, and real estate. We investigate the complexity of the risk spillover effect of Chinese financial markets and the impact of economic policy uncertainty on the level of network contagion of financial risk. The study yields three findings. First, the cross-sectoral risk spillover effects of Chinese financial markets are asymmetric in intensity. The bank sector is systemically important in the risk spillover network. Second, the level of risk stress in the real estate sector has increased in recent years, and it plays an important role in the path of financial risk contagion. Third, Economic policy uncertainty has a significant positive impact on the level of network contagion of financial risk of Chinese financial markets.

scholarly journals Dependence and Risk Spillover among Hedging Assets: Evidence from Bitcoin, Gold, and USD

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Jiang Yu ◽  
Yue Shang ◽  
Xiafei Li
Keyword(s):  
Value At Risk ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Conditional Value At Risk ◽  
Variational Model ◽  
Model Decomposition ◽  
Regulatory Decision ◽  
Short And Long Term ◽  
Risk Spillover Effects

Understanding the dependence and risk spillover among hedging assets is crucial for portfolio allocation and regulatory decision making. Using various copula and conditional Value-at-Risk (CoVaR) measures, this paper quantifies the dependence and risk spillover effects between three traditional and emerging hedging assets: Bitcoin, gold, and USD. Furthermore, we investigate these effects at various short- and long-term horizons using a variational model decomposition (VMD) method. The empirical results show that there is strong negative dependence between gold and USD, but Bitcoin and gold are weakly and positively connected. Secondly, risk spillovers exist only between Bitcoin and gold and between gold and USD. The risk spillover effect between Bitcoin and gold are not stable, that is, if Bitcoin or gold faces the downward or upward risk, both the downward and upward risk of another asset have the chance to increase. The negative risk spillover between gold and USD is stable, especially in long-term horizons. Finally, the risk spillover between Bitcoin and gold as well as between gold and USD are asymmetric at downward and upward market environment.

scholarly journals On Spillover Effect of Systemic Risk of Listed Securities Companies in China Based on Extended CoVaR Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ze-Jiong Zhou ◽  
Shao-Kang Zhang ◽  
Mei Zhang ◽  
Jia-Ming Zhu
Keyword(s):  
Systemic Risk ◽  
Spillover Effect ◽  
Market Value ◽  
Strong Relationship ◽  
Spillover Effects ◽  
Financial Industry ◽  
Short Period ◽  
Securities Industry ◽  
Countermeasures And Suggestions ◽  
Risk Spillover Effects

Based on the daily data from January 2, 2019, to September 30, 2020, this paper uses the extended CoVaR model to measure the spillover effect of systemic risk among top 10 securities companies by market value in China, All Share Brokerage Index, All Share Financials Index, All Share Insurance Index, and CSI Banks Index. The conclusions are as follows: (1) there are risk spillover effects among 10 securities companies, which are asymmetric and bidirectional and highly volatile in a short period of time; (2) the spillover effect of systematic risk of securities companies is not necessarily related to the market value of securities companies but has a strong relationship with the stock market; (3) there are risk spillover effects between the sample securities companies and the four major indexes, but there are significant differences in the size of the spillover effects; (4) the securities industry has a great risk spillover effect on the financial industry, but the risk spillover effect of other financial sectors on the securities industry is very small. Finally, we put forward countermeasures and suggestions.

scholarly journals Research on the Dependence Structure and Risk Spillover of Internet Money Funds Based on C-Vine Copula and Time-Varying t-Copula

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huizi Ma ◽  
Lin Lin ◽  
Han Sun ◽  
Yue Qu
Keyword(s):  
Spillover Effect ◽  
Spillover Effects ◽  
Dependence Structure ◽  
Copula Model ◽  
Time Varying ◽  
Financial Products ◽  
T Copula ◽  
Dependence Relationship ◽  
Vine Copula ◽  
Risk Spillover Effects

Internet money funds (IMFs) are the most widely involved products in the Internet financial products market. This research utilized the C-vine copula model to study the risk dependence structure of IMFs and then introduces the time-varying t-copula model to analyze the risk spillover of diverse IMFs. The results show the following: (1) The risks of Internet-based IMFs, bank-based IMFs, and fund-based IMFs have obvious dependence structure, and the degree of risk dependence among different categories of IMFs is significantly different. (2) There are risk spillover effects among diverse IMFs, and their risk dependence relationship is characterized by cyclical feature. (3) The risk spillover effect among diverse IMFs is pronounced, and dynamic risk dependence between IMFs is characterized by synchronization.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Regional Disparity and Patients Mobility: Benefits and Spillover Effects of the Spatial Network Structure of the Health Services in China

2021 ◽  
Vol 18 (3) ◽  
pp. 1096
Author(s):  
Liping Fu ◽  
Kaibo Xu ◽  
Feng Liu ◽  
Lu Liang ◽  
Zhengmin Wang
Keyword(s):  
Health Economic ◽  
Health Services ◽  
Network Structure ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Health Economy ◽  
Spatial Network ◽  
Spatial Effects ◽  
Medical Resource ◽  
Medical Resources

Background: The distribution of medical resources in China is seriously imbalanced due to imbalanced economic development in the country; unbalanced distribution of medical resources makes patients try to seek better health services. Against this backdrop, this study aims to analyze the spatial network characteristics and spatial effects of China’s health economy, and then find evidence that affects patient mobility. Methods: Data for this study were drawn from the China Health Statistical Yearbooks and China Statistical Books. The gravitational value of China’s health spatial network was calculated to establish a network of gravitational relationships. The social network analysis method was used for centrality analysis and spillover effect analysis. Results: A gravity correlation matrix was constructed among provinces by calculating the gravitational value, indicating the spatial relationships of different provinces in the health economic network. Economically developed provinces, such as Shanghai and Jiangsu, are at the center of the health economic network (centrality degree = 93.333). These provinces also play a strong intermediary role in the network and have connections with other provinces. In the CONCOR analysis, 31 provinces are divided into four blocks. The spillover effect of the blocks indicates provinces with medical resource centers have beneficial effects, while provinces with insufficient resources have obvious spillover effects. Conclusion: There is a significant gap in the geographical distribution of medical resources, and the health economic spatial network structure needs to be improved. Most medical resources are concentrated in economically developed provinces, and these provinces’ positions in the health economic spatial network are becoming more centralized. By contrast, economically underdeveloped regions are at the edge of the network, causing patients to move to provinces with medical resource centers. There are health risks of the increasing pressure to seek medical treatment in developed provinces with abundant medical resources.

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

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