An Integrated  Research of Systemic Risk: Based on Bibliometric Analysis,Network Analysis and Econometric Analysis

Abstract

Systemic risk in the context of the COVID-19 health crisis is a noteworthy issue that has received some attention but requires better understanding. This study presents integrated research on systemic risk using three sub-studies. The first study’s objective is to comprehensively discuss the research status and trends of systemic risk-related publications based on bibliometric analysis and Latent Dirichlet Allocation (LDA), which can provide valuable insights for novice researchers in the field. In the second study, five prominent systemic risk measures (i.e., VaR, ∆CoVaR, MES, SRISK, and volatility) were used as proxies to study the dynamics of systemic risk series and generate corresponding rankings of major Chinese traditional financial sectors (i.e., banking, securities, and insurance). Based on systemic risk rankings, a few important financial institutions were identified. The findings of the second study can provide significant implications for economic policymakers and investors in understanding the importance of a given financial institution. The third study provides fresh empirical evidence for the tourism and hospitality industry and employs econometric models based on international stock markets to investigate the impact of COVID-19 on this industry. Using the Granger causality test and network analysis, we highlight the transformation of interconnectedness during the pandemic.

Date of Award	13 Sept 2024
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Feng Yang (External Supervisor) & Shaoyi Stephen LIAO (Supervisor)