Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles

被引:139
|
作者
Bouri, Elie [1 ]
Gupta, Rangan [2 ]
Lau, Chi Keung Marco [3 ]
Roubaud, David [4 ]
Wang, Shixuan [5 ]
机构
[1] Holy Spirit Univ Kaslik, USEK Business Sch, POB 446, Jounieh, Lebanon
[2] Univ Pretoria, Dept Econ, ZA-0002 Pretoria, South Africa
[3] Univ Huddersfield, Huddersfield Business Sch, Dept Accountancy Finance & Econ, Huddersfield HD1 3DH, W Yorkshire, England
[4] Montpellier Business Sch, ESD, Montpellier, France
[5] Cardiff Univ, Cardiff Business Sch, Cardiff CF10 3EU, S Glam, Wales
关键词
Bitcoin; Global financial stress index; Dependence; Copula Quantiles; DIRECTIONAL PREDICTABILITY; VOLATILITY; MARKETS; MODELS; HEDGE;
D O I
10.1016/j.qref.2018.04.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
We apply different techniques and uncover the quantile conditional dependence between the global financial stress index and Bitcoin returns from July 18, 2010, to December 29, 2017. The results from the copula-based dependence show evidence of right-tail dependence between the global financial stress index and Bitcoin returns. We focus on the conditional quantile dependence and indicate that the global financial stress index strongly Granger-causes Bitcoin returns at the left and right tail of the distribution of the Bitcoin returns, conditional on the global financial stress index. Finally, we use a bivariate cross-quantilogram approach and show only limited directional predictability from the global financial stress index to Bitcoin returns in the medium term, for which Bitcoin can act as a safe-haven against global financial stress. (C) 2018 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:297 / 307
页数:11
相关论文
共 50 条
  • [21] Dependence and mixing for perturbations of copula-based Markov chains
    Longla, Martial
    Nthiani, Mathias Muia
    Ndikwa, Fidel Djongreba
    [J]. STATISTICS & PROBABILITY LETTERS, 2022, 180
  • [22] On a multivariate copula-based dependence measure and its estimation
    Griessenberger, Florian
    Junker, Robert R.
    Trutschnig, Wolfgang
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2022, 16 (01): : 2206 - 2251
  • [23] A Copula-Based Approach for Model Bias Characterization
    Xi, Zhimin
    Hao, Pan
    Fu, Yan
    Yang, Ren-Jye
    [J]. SAE INTERNATIONAL JOURNAL OF PASSENGER CARS-MECHANICAL SYSTEMS, 2014, 7 (02): : 781 - 786
  • [24] Copula-Based Approach to Synthetic Population Generation
    Jeong, Byungduk
    Lee, Wonjoon
    Kim, Deok-Soo
    Shin, Hayong
    [J]. PLOS ONE, 2016, 11 (08):
  • [25] Flood routing via a copula-based approach
    Nazeri Tahroudi, Mohammad
    Ramezani, Yousef
    De Michele, Carlo
    Mirabbasi, Rasoul
    [J]. HYDROLOGY RESEARCH, 2021, 52 (06): : 1294 - 1308
  • [26] A Copula-Based Granger Causality Measure for the Analysis of Neural Spike Train Data
    Hu, Meng
    Li, Wu
    Liang, Hualou
    [J]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2018, 15 (02) : 562 - 569
  • [27] Testing and dating structural changes in copula-based dependence measures
    Stark, Florian
    Otto, Sven
    [J]. JOURNAL OF APPLIED STATISTICS, 2022, 49 (05) : 1121 - 1139
  • [28] Some aspects of modeling dependence in copula-based Markov chains
    Longla, Martial
    Peligrad, Magda
    [J]. JOURNAL OF MULTIVARIATE ANALYSIS, 2012, 111 : 234 - 240
  • [29] Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach
    Arreola Hernandez, Jose
    Hammoudeh, Shawkat
    Duc Khuong Nguyen
    Al Janabi, Mazin A. M.
    Carlos Reboredo, Juan
    [J]. APPLIED ECONOMICS, 2017, 49 (25) : 2409 - +
  • [30] A Copula-Based Non-parametric Measure of Regression Dependence
    Dette, Holger
    Siburg, Karl F.
    Stoimenov, Pavel A.
    [J]. SCANDINAVIAN JOURNAL OF STATISTICS, 2013, 40 (01) : 21 - 41