Dependency and causal relationship between 'Bitcoin' and financial asset classes: A Bayesian network approach

被引:0
|
作者
Mroua, Mourad [1 ]
Souissi, Nada [2 ]
Donia, Mrabet [1 ]
机构
[1] Univ Sfax, Inst Higher Commercial Studies, Sfax, Tunisia
[2] Univ Sfax, Fac Econ & Management, Sfax, Tunisia
关键词
Bayesian network; Bitcoin; conventional markets; GARCH model; Markov switching; parametric and structure learning; GOLD; VOLATILITY;
D O I
10.1002/ijfe.2895
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study employs the Bayesian Networks (BN) and the wavelet coherence approaches to invest the relationship between Bitcoin volatility and financial asset classes (MSCI world equity index, S&P Goldman Sachs Commodity Index [GSCI], US index and Investment Grade Corporate Bond Index ETF [PIMCO]) using daily data for the period from August 2011 to October 2021. The results show that the causal relationship between Bitcoin and other financial assets varies depending on the market states. During the low volatility periods, Bitcoin has a stronger impact on the GSCI, while during the stability periods, it has a direct effect on the US index and the MSCI world index. In contrast, during high volatility periods, Bitcoin has a direct impact on both the GSCI and PIMCO indices. The key findings enabled us to provide implications for US investors to promote asset allocation and risk management covering both Bitcoin and traditional financial markets. The results suggest that policymakers should watch Botcoin closely to preserve financial stability.
引用
收藏
页码:4888 / 4901
页数:14
相关论文
共 39 条
  • [21] Studding relationship between bitcoin, exchange rate and financial development: a panel data analysis
    Sadraoui, Tarek
    Nasr, Ahlem
    Mgadmi, Nidhal
    INTERNATIONAL JOURNAL OF MANAGERIAL AND FINANCIAL ACCOUNTING, 2021, 13 (3-4) : 232 - 252
  • [22] A causal Bayesian network approach for consumer product safety and risk assessment
    Hunte, Joshua L.
    Neil, Martin
    Fenton, Norman E.
    JOURNAL OF SAFETY RESEARCH, 2022, 80 : 198 - 214
  • [23] The relationship between bitcoin and energy commodities: AutoRegressive distributed lag approach
    Jouini, Fathi
    Messai, Ahlem Selma
    Derbali, Abdelkader Mohamed Sghaier
    INTERNATIONAL JOURNAL OF FINANCIAL ENGINEERING, 2022, 09 (04)
  • [24] Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach
    Guidolin, Massimo
    Hansen, Erwin
    Pedio, Manuela
    JOURNAL OF FINANCIAL MARKETS, 2019, 45 : 83 - 114
  • [25] Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach
    Zhang, Yue-Jun
    Bouri, Elie
    Gupta, Rangan
    Ma, Shu-Jiao
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2021, 55
  • [26] Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach
    Ji, Qiang
    Bouri, Elie
    Gupta, Rangan
    Roubaud, David
    QUARTERLY REVIEW OF ECONOMICS AND FINANCE, 2018, 70 : 203 - 213
  • [27] ANALYZING THE CAUSAL RELATIONSHIP FOR AN EFFECTIVE REMEDIAL EDUCATION BASED ON BAYESIAN NETWORK: A CASE STUDY
    Arakawa, Toshiya
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2021, 17 (04): : 1421 - 1433
  • [28] A Bayesian network approach to power system asset management for transformer dissolved gas analysis
    Tang, W. H.
    Lu, Z.
    Wu, Q. H.
    2008 THIRD INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES, VOLS 1-6, 2008, : 1460 - 1466
  • [29] The connectedness between meme tokens, meme stocks, and other asset classes: Evidence from a quantile connectedness approach
    Yousaf, Imran
    Pham, Linh
    Goodell, John W.
    JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2023, 82
  • [30] Exploring the relationship between Bitcoin price and network's hashrate within endogenous system
    Kubal, Jan
    Kristoufek, Ladislav
    INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 2022, 84