Please use this identifier to cite or link to this item:
Appears in Collections:Accounting and Finance Journal Articles
Peer Review Status: Refereed
Title: Complex Network Analysis of Volatility Spillovers between Global Financial Indicators and G20 Stock Markets
Author(s): Korkusuz, Burak
McMillan, David
Kambouroudis, Dimos
Contact Email:
Keywords: Volatility spillover
Complex network theory
Global financial indicators
G20 stock markets
Issue Date: 10-Sep-2022
Date Deposited: 26-Jul-2022
Citation: Korkusuz B, McMillan D & Kambouroudis D (2022) Complex Network Analysis of Volatility Spillovers between Global Financial Indicators and G20 Stock Markets. <i>Empirical Economics</i>.
Abstract: This paper analyses the dynamic transmission mechanism of volatility spillovers between key global financial indicators and G20 stock markets. To examine volatility spillover relations, we combine a bivariate GARCH-BEKK model with complex network theory. Specifically, we construct a volatility network of international financial markets utilising the spatial connectedness of spillovers (consisting of nodes and edges). The findings show that spillover relations between global variables and G20 markets varies significantly across five identified sub-periods. Notably, networks are much denser in crisis periods compared to non-crisis periods. In comparing two crisis periods, Global Financial Crisis (2008) and Covid-19 Crisis (2020) periods, the network statistics suggest that volatility spillovers in the latter period are more transitive and intense than the former. This suggests that financial volatility spreads more rapidly and directly through key financial indicators to the G20 stock markets. For example, oil and bonds are the largest volatility senders, while the markets of Saudi Arabia, Russia, South Africa, and Brazil are the main volatility receivers. In the former crisis, the source of financial volatility concentrates primarily in the US, Australia, Canada, and Saudi Arabia, which are the largest volatility senders and receivers. China emerges as generally the least sensitive market to external volatility.
DOI Link: 10.1007/s00181-022-02290-w
Rights: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
Licence URL(s):

Files in This Item:
File Description SizeFormat 
s00181-022-02290-w.pdfFulltext - Published Version1.4 MBAdobe PDFView/Open

This item is protected by original copyright

A file in this item is licensed under a Creative Commons License Creative Commons

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved

If you believe that any material held in STORRE infringes copyright, please contact providing details and we will remove the Work from public display in STORRE and investigate your claim.