Tail risk contagion and multiscale spillovers in the green finance index and large US technology stocks

IF 7.5 1区 经济学 Q1 BUSINESS, FINANCE
Hongjun Zeng, Mohammad Zoynul Abedin, Brian Lucey, Shenglin Ma
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Abstract

Our purpose is to check the dynamic asymmetric volatility connectedness among the Green Finance Index and six large US technology stocks. The QVAR connectedness framework, the quantile Granger causality test, the TVP-VAR frequency connectedness framework, and the quantile-on-quantile regression (QQR) function were employed to measure the cross-frequency and quantile risk dependencies among these indices. The findings show that: (1) the volatility connectedness effect is higher at extreme tails. In addition, the dynamic spillover between the Green financial index and large US technology stocks is strengthened during bullish market conditions. (2). Net risk spillover characteristics across markets show cyclicality and heterogeneity. The S&P 500 ESG index and Microsoft are the dominant sources of risk. In contrast, the S&P Green Bond Index and Apple act as net recipients of spillovers. (3). Connectedness networks across quartiles exhibit asymmetric behavior. (4). When considering all quartiles, there was a significant Granger causality between the Green Finance Index and major US technology firms. (5). The results of frequency spillovers indicate that long-term frequency spillovers predominate over short-term frequency spillover. The S&P 500 ESG Index contributed risk across frequencies, while green bonds acted as a receiver of risk across frequencies. (6) Utilising the multivariate QQR method, we find the impact of the green finance index on US technology stocks risk exhibited significant non-linear and asymmetric characteristics, demonstrating pronounced cross-quantile heterogeneity. Our empirical findings held practical significance for heterogeneous market participants concerned with the risks associated with green finance and high-tech assets across different investment horizons and market conditions.
绿色金融指数和美国大型科技股的尾部风险传染和多尺度溢出效应
我们的目的是检验绿色金融指数与美国六大科技股之间的动态非对称波动关联性。我们采用 QVAR 连接性框架、量子格兰杰因果检验、TVP-VAR 频率连接性框架和量子对量子回归(QQR)函数来衡量这些指数之间的跨频率和量子风险依赖性。研究结果表明(1) 在极端尾部,波动性关联效应更高。此外,在市场看涨时,绿色金融指数与美国大型科技股之间的动态溢出效应增强。(2).不同市场的净风险溢出特征呈现出周期性和异质性。S&P 500 ESG 指数和微软是主要的风险来源。相反,S&P 绿色债券指数和苹果公司则是风险溢出的净接受者。(3).四分位数之间的连通性网络表现出不对称行为。(4).当考虑所有四分位数时,绿色金融指数与美国主要科技公司之间存在显著的格兰杰因果关系。(5).频率溢出效应的结果表明,长期频率溢出效应优于短期频率溢出效应。S&P 500 ESG 指数贡献了跨频率的风险,而绿色债券则是跨频率风险的接收者。(6) 利用多元 QQR 方法,我们发现绿色金融指数对美国科技股风险的影响呈现出显著的非线性和非对称特征,表现出明显的跨量纲异质性。我们的实证研究结果对于关注绿色金融和高科技资产在不同投资期限和市场条件下相关风险的异质市场参与者具有实际意义。
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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