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

IF 2.8 3区 经济学 Q2 BUSINESS, FINANCE
Mourad Mroua, Nada Souissi, Mrabet Donia
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引用次数: 0

Abstract

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.
“比特币”和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,研究比特币波动率与金融资产类别(MSCI世界股票指数、标普高盛商品指数[GSCI]、美国指数和投资级公司债券指数ETF [PIMCO])之间的关系。结果表明,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的影响更大,而在稳定期,比特币对美国指数和MSCI世界指数有直接影响。相比之下,在高波动性时期,比特币对GSCI和PIMCO指数都有直接影响。这些关键发现使我们能够为美国投资者提供启示,以促进比特币和传统金融市场的资产配置和风险管理。研究结果表明,政策制定者应该密切关注Botcoin,以保持金融稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
143
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