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About
President
Governance
Partner Institutions
Visit
People
Management
Faculty
Postdocs
Visiting Scholars
Staff
Research
Research Groups
Courses
Seminars
Join Us
Faculty
Postdocs
Students
Events
Conferences
Workshops
Forum
Life @ BIMSA
Accommodation
Transportation
Facilities
Tour
News
News
Announcement
Downloads
Qiuzhen College, Tsinghua University
Yau Mathematical Sciences Center, Tsinghua University (YMSC)
Tsinghua Sanya International  Mathematics Forum (TSIMF)
Shanghai Institute for Mathematics and  Interdisciplinary Sciences (SIMIS)
BIMSA > BIMSA Digital Economy Lab Seminar A Measurement of Financial Network Connectedness
A Measurement of Financial Network Connectedness
Organizers
Li Yan Han , Zhen Li , Qing Fu Liu , Fei Long , Ke Tang
Speaker
Junda Wu
Time
Monday, October 28, 2024 3:20 PM - 4:20 PM
Venue
A3-2-303
Online
Zoom 230 432 7880 (BIMSA)
Abstract
This talk introduces one of the most popular network methodologies currently used in economics and finance , FX Diebold, K Yilmaz(2009) proposed this method subsequently refined through a series of papers (DY2012, DY2014, DY2018), which is constructed based on forecast-error variance decompositions (FEVD) from generalized VAR models. This approach can intuitively characterize both static and dynamic connectedness relationships among different asset classes and companies across different countries. In DY2014, the authors recognized that their methodology belongs to the broader field of network science, with their spillover effect matrix being equivalent to an adjacency matrix. DY2018 further enhanced the framework by incorporating LASSO, elastic net, and other methods to shrink, select, and estimate high-dimensional networks. Building upon these works, Gabauer and Gupta (2018) extended the methodology by replacing the GVAR model with a TVP-VAR model, thereby eliminating the need for rolling windows. This talk also implements some sample applications using the R package 'ConnectednessApproach'.
Speaker Intro
Junda Wu is a PhD student at BIMSA and UCAS. His research interests include digital economy, applications of artificial intelligence in economics, and cross-market risk spillovers.
Beijing Institute of Mathematical Sciences and Applications
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