Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency

被引:68
作者
Qureshi, Saba [1 ]
Aftab, Muhammad [2 ]
Bouri, Elie [3 ]
Saeed, Tareq [4 ]
机构
[1] Univ Sindh, Inst Business Adm, Jamshoro, Pakistan
[2] COMSATS Univ Islamabad, Dept Management Sci, Islamabad, Pakistan
[3] Holy Spirit Univ Kaslik, USEK Business Sch, POB 446, Jounieh, Lebanon
[4] King Abdulaziz Univ, Fac Sci, Dept Math, Nonlinear Anal & Appl Math NAAM Res Grp, Jeddah, Saudi Arabia
关键词
Cryptocurrencies; Wavelet analysis; Interdependencies; Market integration; Contagion; SAFE HAVEN; WAVELET COHERENCE; BITCOIN; SPILLOVERS; PRICE; EXCHANGE; HEDGE;
D O I
10.1016/j.physa.2020.125077
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The extreme price swings and complexity in cryptocurrency markets drives multifarious research into co-movements, in both time and frequency, among cryptocurrencies. In this paper, we investigate the dynamics of multiscale interdependencies among five leading and liquid cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash) using wavelet-based analyses that account for the heterogeneous behaviour of crypto-traders and crypto-investors. The results provide evidence of high levels of dependency from 2016 to 2018 at daily frequency scales. The cross wavelet transforms demonstrate Ripple and Ethereum to be trivial origins of market contagion. The results of wavelet coherence confirm the short-run and long-run market integration among some cryptocurrency pairs. However, the coherence is found to fluctuate at higher frequencies and be significantly stable at lower frequencies. Furthermore, the switch in the lead and lag relations of cryptocurrency returns suggests alternating time and frequency interdependencies. Our findings are useful to scale-conscious traders and multi-prospect (various investment horizon) investors and portfolio managers. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页数:15
相关论文
共 53 条
[1]  
Aftab M., 2019, EC INTEGRATION CURRE
[2]   Using wavelets to decompose the time-frequency effects of monetary policy [J].
Aguiar-Conraria, Luis ;
Azevedo, Nuno ;
Soares, Maria Joana .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2008, 387 (12) :2863-2878
[3]   California's carbon market and energy prices: a wavelet analysis [J].
Aguiar-Conraria, Luis ;
Soares, Maria Joana ;
Sousa, Rita .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2018, 376 (2126)
[4]  
[Anonymous], 2000, Wavelet Methods for Time Series Analysis
[5]   Bitcoin: Medium of exchange or speculative assets? [J].
Baur, Dirk G. ;
Hong, KiHoon ;
Lee, Adrian D. .
JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2018, 54 :177-189
[6]   Price dynamics and speculative trading in bitcoin [J].
Blau, Benjamin M. .
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2017, 41 :493-499
[7]   Evidence of interdependence and contagion using a frequency domain framework [J].
Bodart, Vincent ;
Candelon, Bertrand .
EMERGING MARKETS REVIEW, 2009, 10 (02) :140-150
[8]   Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis [J].
Bouri, Elie ;
Shahzad, Syed Jawad Hussain ;
Roubaud, David ;
Kristoufek, Ladislav ;
Lucey, Brian .
QUARTERLY REVIEW OF ECONOMICS AND FINANCE, 2020, 77 :156-164
[9]   The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages [J].
Bouri, Elie ;
Lucey, Brian ;
Roubaud, David .
FINANCE RESEARCH LETTERS, 2020, 33
[10]   Co-explosivity in the cryptocurrency market [J].
Bouri, Elie ;
Shahzad, Syed Jawad Hussain ;
Roubaud, David .
FINANCE RESEARCH LETTERS, 2019, 29 :178-183