Dependence of green energy markets on big data and other fourth industrial revolution technologies

IF 5.4 2区 经济学 Q1 BUSINESS, FINANCE Journal of International Financial Markets Institutions & Money Pub Date : 2024-10-01 DOI:10.1016/j.intfin.2024.102061
Ramzi Benkraiem , Khaled Guesmi , Gideon Ndubuisi , Christian Urom , Samuel Vigne
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Abstract

This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.
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绿色能源市场依赖大数据和其他第四次工业革命技术
本文分析了第四次工业革命技术市场(包括大数据和人工智能、区块链和金融技术)与全球和地区(美国、欧洲和亚洲)绿色能源市场之间的依赖性和关联性。特别是,我们使用跨谱一致性和Quantile-VAR连通性方法,考虑了这些市场在不同市场条件和投资期限下的收益和波动的动态依赖性。我们的分析得出了三个主要结果。首先,收益率依赖性相对强于波动率依赖性,而且在大多数时间尺度上,技术市场以及欧洲和亚洲地区绿色能源指数的收益率依赖性更强。其次,在极端市场条件下,收益率和波动率的关联性比正常市场条件下更强。除非在市场看涨的情况下,否则波动性的关联性似乎小于收益率的关联性,这意味着在正常和看跌的市场时期,市场波动性风险在这些市场中的扩散力度小于收益率风险。第三,地缘政治风险、商业环境、经济政策、固定收入以及石油和黄金市场的不确定性是回报率和波动率关联度的重要预测因素。总之,我们的研究结果为对现代技术和绿色资产投资组合感兴趣的短期和长期投资者提供了重要启示。研究还强调了市场和宏观经济因素在冲击传播中的作用及其对低碳转型的影响。
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
6.60
自引率
10.00%
发文量
142
期刊介绍: International trade, financing and investments, and the related cash and credit transactions, have grown at an extremely rapid pace in recent years. The international monetary system has continued to evolve to accommodate the need for foreign-currency denominated transactions and in the process has provided opportunities for its ongoing observation and study. The purpose of the Journal of International Financial Markets, Institutions & Money is to publish rigorous, original articles dealing with the international aspects of financial markets, institutions and money. Theoretical/conceptual and empirical papers providing meaningful insights into the subject areas will be considered. The following topic areas, although not exhaustive, are representative of the coverage in this Journal. • International financial markets • International securities markets • Foreign exchange markets • Eurocurrency markets • International syndications • Term structures of Eurocurrency rates • Determination of exchange rates • Information, speculation and parity • Forward rates and swaps • International payment mechanisms • International commercial banking; • International investment banking • Central bank intervention • International monetary systems • Balance of payments.
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