Interconnectedness of cryptocurrency markets: an intraday analysis of volatility spillovers based on realized volatility decomposition

被引:0
|
作者
Ben Ameur, Hachmi [1 ]
Ftiti, Zied [2 ]
Louhichi, Wael [3 ]
机构
[1] INSEEC Grande Ecole, OMNES Educ, Paris, France
[2] EDC Paris Business Sch, OCRE Res Lab, Paris, France
[3] ESSCA Sch Management, Paris, France
关键词
Diebold and Yilmaz; Jump; Co-jump; Continuous volatility; Contagion; COVID-19; crisis; IMPULSE-RESPONSE ANALYSIS; BITCOIN; JUMP; INEFFICIENCY; COMPONENTS;
D O I
10.1007/s10479-023-05757-w
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The cryptocurrency market has undergone significant turbulence, characterized by enormous volatility shifts, as recently experienced during the COVID-19 shock. Although there is an abundant literature dealing with various aspects of cryptocurrencies, little attention has been devoted to understanding the interconnectedness among different cryptocurrencies, particularly the role of abrupt changes. This paper aims to fill this gap by conducting an intraday analysis to assess the contagion hypothesis within the cryptocurrency markets, with particular focus on the aprubt changes and whether it is a driver of co-aprubt changes in other markets. Specfically, we investigate four major cryptocurrencies (Bitcoin, Ethereum, Ethereum Classic, and Ripple) both prior to and during the COVID-19 shock, April 2019 to September 2020. Using the Diebold and Yilmaz methodology, we decompose the realized volatility into continuous and jump components, and examine how these spillovers evolve across cryptocurrency markets before and during the COVID-19 crisis. Our findings reveal that while the volatility and returns spillovers across the cryptocurrency market escalate during the crisis, there is a notable decrease in the jumps and co-jumps between cryptocurrencies. This suggests that the heightened interdependency observed is not rooted in fundamental factors. Morever, our findings show that spillover is especially prominent in the continuous part of the realised volatility dynamic. Notably, XRP emerges as the predominant transmitter in the context of continuous part of the realized volatility. Our study contributes to the emerging literature on the interconnectedness of price movement/co-mouvement across cryptocurrencies, offers a novel adaptation of the Diebold and Yilmaz methodology to capture the unique features of cryptocurrency prices.
引用
收藏
页码:757 / 779
页数:23
相关论文
共 50 条
  • [41] Volatility Spillovers and Linkages in Asian Stock Markets
    Chow, Hwee Kwan
    EMERGING MARKETS FINANCE AND TRADE, 2017, 53 (12) : 2770 - 2781
  • [42] Analysis of meat price volatility and volatility spillovers in Finland
    Ben Abdallah, Marwa
    Farkas, Maria Fekete
    Lakner, Zoltan
    AGRICULTURAL ECONOMICS-ZEMEDELSKA EKONOMIKA, 2020, 66 (02): : 84 - 91
  • [43] Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns
    Zhao, Xiaojun
    Zhang, Na
    Zhang, Yali
    Xu, Chao
    Shang, Pengjian
    JOURNAL OF EMPIRICAL FINANCE, 2024, 77
  • [44] Volatility spillovers among MIST stock markets
    Sevinc, Deniz
    DATA SCIENCE IN FINANCE AND ECONOMICS, 2022, 2 (02): : 80 - 95
  • [45] Realized volatility and correlation in energy futures markets
    Wang, Tao
    Wu, Jingtao
    Yang, Jian
    JOURNAL OF FUTURES MARKETS, 2008, 28 (10) : 993 - 1011
  • [46] Why cryptocurrency markets are inefficient: The impact of liquidity and volatility
    Al-Yahyaee, Khamis Hamed
    Mensi, Walid
    Ko, Hee-Un
    Yoon, Seong-Min
    Kang, Sang Hoon
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2020, 52
  • [47] The information content of implied volatility in light of the jump/continuous decomposition of realized volatility
    Giot, Pierre
    Laurent, Sebastien
    JOURNAL OF FUTURES MARKETS, 2007, 27 (04) : 337 - 359
  • [48] Analysis of Realized Volatility in Superstatistics
    Takaishi, Tetsuya
    EVOLUTIONARY AND INSTITUTIONAL ECONOMICS REVIEW, 2010, 7 (01) : 89 - 99
  • [49] Volatility and dependence in cryptocurrency and financial markets: a copula approach
    Liu, Jinan
    Serletis, Apostolos
    STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, 2024, 28 (01): : 119 - 149
  • [50] Forecasting realized exchange rate volatility by decomposition
    Lanne, Markku
    INTERNATIONAL JOURNAL OF FORECASTING, 2007, 23 (02) : 307 - 320