A comparative study of dynamic risk spillovers among financial sectors in China before and after the epidemic

This paper takes the unexpected event of the new coronavirus as the research background, selects the daily closing price data of the financial sectors (banking, insurance, securities, and multifinance) from 20 June 2017 to 31 December 2023. It then applies the TVP-VAR-DY model to empirically study the risk spillover effect among financial sectors. The study identified three distinct stages: before, during, and after the epidemic. It revealed that the total systematic spillover exhibited an initial increase, followed by a subsequent decrease. Notably, the fluctuation in this phenomenon intensified significantly during the epidemic. The securities sector emerged as the most susceptible to spillover risks from other sectors and, in turn, the most vulnerable to risk contagion from other sectors. Conversely, the banking sector demonstrated relative stability. Furthermore, the multifinance sector is more susceptible to risk contagion from other sectors during the pre-epidemic and mid-epidemic stages. However, following the epidemic, as the economy has not yet fully recovered, the multifinance sector is more likely to experience spillover risks from other sectors, and the insurance sector also primarily acts as a risk spillover. Finally, five different lag orders were selected to test the robustness of the empirical results of the model. The test results demonstrated that the model was valid and the results were feasible.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2024-12-10
DOI
https://doi.org/10.1371/journal.pone.0314071
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A comparative study of dynamic risk spillovers among financial sectors in China before and after the epidemic

Junfu Cui, Hubin Ma, Xu Hui Simon Shen, Cuicui Liu et al.
PLoS ONE
Market Dynamics and Volatility
article

A comparative study of dynamic risk spillovers among financial sectors in China before and after the epidemic

Junfu Cui, Hubin Ma, Xu Hui Simon Shen, Cuicui Liu, Xiangrong Wang
article en

Abstract

This paper takes the unexpected event of the new coronavirus as the research background, selects the daily closing price data of the financial sectors (banking, insurance, securities, and multifinance) from 20 June 2017 to 31 December 2023. It then applies the TVP-VAR-DY model to empirically study the risk spillover effect among financial sectors. The study identified three distinct stages: before, during, and after the epidemic. It revealed that the total systematic spillover exhibited an initial increase, followed by a subsequent decrease. Notably, the fluctuation in this phenomenon intensified significantly during the epidemic. The securities sector emerged as the most susceptible to spillover risks from other sectors and, in turn, the most vulnerable to risk contagion from other sectors. Conversely, the banking sector demonstrated relative stability. Furthermore, the multifinance sector is more susceptible to risk contagion from other sectors during the pre-epidemic and mid-epidemic stages. However, following the epidemic, as the economy has not yet fully recovered, the multifinance sector is more likely to experience spillover risks from other sectors, and the insurance sector also primarily acts as a risk spillover. Finally, five different lag orders were selected to test the robustness of the empirical results of the model. The test results demonstrated that the model was valid and the results were feasible.

PLoS ONEVol. 19(12)
Shandong Women’s University (CN), Shandong University of Science and Technology (CN)
Natural Science Foundation of Shandong Province
Openalex Percentile: Top 72%
Market Dynamics and Volatility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.