Dynamic Connectedness and Volatility Spillover Effects of Indian Stock Market with International Stock Markets: An Empirical Investigation Using DCC GARCH

被引:0
|
作者
Sainath, A. R. [1 ,2 ]
Gnanendra, M. [1 ,2 ,4 ]
Mohanasundaram, T. [3 ]
James, Leena [4 ]
Misra, Sheelan [1 ,2 ]
机构
[1] New Horizon Coll Engn, Dept Management Studies, Bangalore, Karnataka, India
[2] New Horizon Coll Engn, Res Ctr, Bangalore, Karnataka, India
[3] Ramiah Inst Technol, Dept Management Studies, Bangalore, Karnataka, India
[4] CHRIST, Sch Business & Management, Bangalore, Karnataka, India
关键词
Dynamic connectedness; Volatility spillover; Indian stock market; International stock market; DCC-GARCH; Contagion effects; Interdependence; Emerging economies;
D O I
10.46585/sp31011691
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study employs the DCC-GARCH model to investigate the dynamic connectedness between the Indian and significant global stock markets. Specifically, we examine daily log returns data of the National Stock Exchange (NSE) index and several international indices, including the United States, Australia, China, Germany, England, Japan, and Taiwan. Our analysis indicates a significant level of volatility spillover between the Indian stock market and the international stock market. Notably, we observe a significant positive spillover effect from the S&P 500 and FTSE 100 to the Indian stock market, suggesting contagion effects. Additionally, we find bidirectional spillover between the Indian stock market and the Nikkei 225 and Hang Seng, indicating a high level of interdependence between these markets. Our research contributes to the growing literature on the dynamic connectedness of stock markets and has important implications for policymakers and investors in emerging economies such as India. Overall, this study provides valuable insights into the nature and extent of spillover effects between the Indian and international stock markets.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] DCC Analysis of the Two Stock Market Returns by a Threshold Model: Empirical Study of the Stock Markets in Japan and Canada
    Horng, Wann-Jyi
    Hu, Tien-Chung
    Huang, Ming-Chi
    AUTOMATION EQUIPMENT AND SYSTEMS, PTS 1-4, 2012, 468-471 : 181 - +
  • [42] Geopolitical risk and stock market volatility in emerging markets: A GARCH-MIDAS approach
    Salisu, Afees A.
    Ogbonna, Ahamuefula E.
    Lasisi, Lukman
    Olaniran, Abeeb
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2022, 62
  • [43] An empirical analysis of the volatility spillover effect between primary stock markets abroad and China
    Ke, Jian
    Wang, Liming
    Murray, Louis
    JOURNAL OF CHINESE ECONOMIC AND BUSINESS STUDIES, 2010, 8 (03) : 315 - 333
  • [44] Return and volatility spillover effects between the Turkey and the Russia stock market
    Kutlu, Melih
    Karakaya, Aykut
    JOURNAL OF ECONOMIC AND ADMINISTRATIVE SCIENCES, 2021, 37 (04) : 456 - 470
  • [45] Volatility Analysis for Chinese Stock Market Using GARCH Type Models
    Yin Zehua
    Zhang Lei
    Liu David
    DATA PROCESSING AND QUANTITATIVE ECONOMY MODELING, 2010, : 186 - 193
  • [46] Global Stock Market Volatility and Its Spillover on the Indian Stock Market: A Study Before and During the COVID-19 Period
    Prasad, Saroj S.
    Verma, Ashutosh
    Bakhshi, Priti
    Prasad, Shantanu
    FIIB BUSINESS REVIEW, 2023,
  • [47] Islamic equity market integration and volatility spillover between emerging and US stock markets
    Majdoub, Jihed
    Mansour, Walid
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2014, 29 : 452 - 470
  • [48] Dynamic return and volatility connectedness between commodities and Islamic stock market indices
    Bahloul, Slah
    Khemakhem, Imen
    RESOURCES POLICY, 2021, 71
  • [49] Dynamic return and volatility connectedness between commodities and Islamic stock market indices
    Bahloul, Slah
    Khemakhem, Imen
    Resources Policy, 2021, 71
  • [50] Spillovers of international interest rate swap markets and stock market volatility
    Lee, Hsiu-Chuan
    Hsu, Chih-Hsiang
    Chien, Cheng-Yi
    MANAGERIAL FINANCE, 2016, 42 (10) : 943 - 962