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

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-10-30 DOI:10.1002/ijfe.2895
Mourad Mroua, Nada Souissi, Mrabet Donia
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Abstract

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.

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比特币 "与金融资产类别之间的依赖和因果关系:贝叶斯网络方法
本研究采用贝叶斯网络(BN)和小波相干性方法,利用 2011 年 8 月至 2021 年 10 月期间的每日数据,研究比特币波动与金融资产类别(MSCI 全球股票指数、S&P 高盛商品指数 [GSCI]、美国指数和投资级公司债券指数 ETF [PIMCO])之间的关系。结果显示,比特币与其他金融资产之间的因果关系因市场状态而异。在低波动期,比特币对 GSCI 指数的影响更大,而在稳定期,比特币对美国指数和 MSCI 全球指数有直接影响。相反,在高波动期,比特币对 GSCI 和 PIMCO 指数都有直接影响。主要研究结果使我们能够为美国投资者提供促进资产配置和风险管理的启示,涵盖比特币和传统金融市场。研究结果表明,政策制定者应密切关注比特币,以维护金融稳定。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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