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
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