Dynamic volatility spillover and network connectedness across ASX sector markets

被引:26
作者
Choi, Ki-Hong [1 ]
Mciver, Ron P. [2 ]
Ferraro, Salvatore [3 ]
Xu, Lei [2 ]
Kang, Sang Hoon [4 ]
机构
[1] Pusan Natl Univ, Inst Econ & Int Trade, Busan 46241, South Korea
[2] Univ South Australia, UniSA Business, GPO Box 2471, Adelaide, SA 5001, Australia
[3] Global Founders Funds Management, Melbourne, Australia
[4] Pusan Natl Univ, Dept Business Adm, Busan, South Korea
基金
新加坡国家研究基金会;
关键词
Dynamic volatility spillovers; Financial crisis; Connectedness network; Sector indices; C58; F37; G14; G15; Q31; IMPULSE-RESPONSE ANALYSIS; STOCK MARKETS; SYSTEMIC RISK; CRUDE-OIL; BRICS; US; TRANSMISSION; RETURN;
D O I
10.1007/s12197-021-09544-w
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study measures dynamic volatility spillovers and identifies the connectedness network across 11 Australian Securities Exchange (ASX) sector indices using the spillover index methodology of Diebold and Yilmaz (J Econ 182:119-134, 2014). Additionally, we visualize volatility connectedness relationships as links within a complex network to capture the propagation path of volatility connectedness across the 11 ASX sectors. Our results indicate that recent financial crises intensified the degree of volatility connectedness across the 11 ASX sectors, supporting the contagion hypothesis. Importantly, the financial sector is the main transmitter of volatility connectedness across the 11 ASX sector markets.
引用
收藏
页码:677 / 691
页数:15
相关论文
共 41 条
[1]  
Adrian T., Journal of Financial Intermediation
[2]   Directional spillovers from the US and the Saudi market to equities in the Gulf Cooperation Council countries [J].
Awartani, Basel ;
Maghyereh, Aktham I. ;
Al Shiab, Mohammad .
JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2013, 27 :224-242
[3]  
Balli F., 2016, J ECON FINANC-US, V40, P568, DOI [10.1007/s12197-015-9326-6, DOI 10.1007/S12197-015-9326-6]
[4]   Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees [J].
Barbi, A. Q. ;
Prataviera, G. A. .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 523 :876-885
[5]  
Basu S., 2019, A system-wide approach to measure connectivity in the financial sector, DOI [10.2139/ssrn.2816137, DOI 10.2139/SSRN.2816137]
[6]   Networks of volatility spillovers among stock markets [J].
Baumohl, Eduard ;
Kocenda, Evzen ;
Lyocsa, Stefan ;
Vyrost, Tomas .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 490 :1555-1574
[7]   Econometric measures of connectedness and systemic risk in the finance and insurance sectors [J].
Billio, Monica ;
Getmansky, Mila ;
Lo, Andrew W. ;
Pelizzon, Loriana .
JOURNAL OF FINANCIAL ECONOMICS, 2012, 104 (03) :535-559
[8]  
Budd B.Q., 2017, Journal o f Econom icsandFinance, V1, DOI DOI 10.1007/S12197-017-9391-0
[9]  
CAPORALE G., 2006, Journal ofEconomics and Finance, V30, P376
[10]   Eurozone network "Connectedness" after fiscal year 2008 [J].
Cimini, Riccardo .
FINANCE RESEARCH LETTERS, 2015, 14 :160-166