The tail connectedness among conventional, religious, and sustainable investments: An empirical evidence from neural network quantile regression approach

Xin Jin, Bisharat Hussain Chang, Chaosheng Han, Mohammed Ahmar Uddin
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Abstract

Financial markets are highly unpredictable and often associated with tail risks. This study examines the tail connectivity among three distinct markets—conventional, religious, and sustainable—and uses a new neural network quantile regression technique to quantify their risk exposure. The findings suggest that traditional and religious investments have the greatest tail risk exposure during crises, emphasising the importance of diversification using sustainable investments. The Systematic Network Risk Index identifies intense events, such as the COVID-19 pandemic, the European debt crisis, and the global financial crisis, as having the greatest tail risk. The Systematic Fragility Index finds the Islamic stocks during the COVID-19 crisis and the conventional stock market before the pandemic to the highly vulnerable markets. On the other hand, the Systemic Hazard Index identifies Islamic stocks as the primary source of systemic risk. The study concludes by providing implications for decision-makers, regulatory authorities, investors, players in the financial system, and investment managers to diversify their risk by utilising green/sustainable investments.
传统投资、宗教投资和可持续投资之间的尾部关联性:神经网络量化回归方法的经验证据
金融市场具有高度不可预测性,往往与尾部风险相关联。本研究探讨了传统、宗教和可持续这三个不同市场之间的尾部关联性,并使用了一种新的神经网络量化回归技术来量化它们的风险敞口。研究结果表明,传统投资和宗教投资在危机期间的尾部风险最大,这强调了利用可持续投资进行多样化的重要性。系统网络风险指数认为,COVID-19 大流行病、欧洲债务危机和全球金融危机等激烈事件的尾部风险最大。系统脆弱性指数发现,COVID-19 危机期间的伊斯兰股票和大流行病之前的传统股票市场是高度脆弱的市场。另一方面,系统危害指数将伊斯兰股票确定为系统风险的主要来源。研究最后为决策者、监管机构、投资者、金融体系参与者和投资经理提供了利用绿色/可持续投资分散风险的启示。
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