Interconnectedness between electricity and artificial intelligence-based markets during the crisis periods: Evidence from the TVP-VAR approach

被引:0
|
作者
Yousaf, Imran [1 ,2 ]
Ohikhuare, Obaika M. [3 ]
Li, Yong [4 ]
Li, Yanshuang [5 ]
机构
[1] Prince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
[2] Univ Jordan, Sch Business, Amman, Jordan
[3] Fed Univ Agr, Dept Econ, Abeokuta, Ogun State, Nigeria
[4] Shanghai Normal Univ, Tianhua Coll, Shanghai, Peoples R China
[5] Dongbei Univ Finance & Econ, Sch Fintech, Dalian, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
TVP-VAR; Return spillover; Spillover drivers; AI-based stocks; Electricity market crisis; VOLATILITY SPILLOVERS; SAFE HAVEN; CRUDE-OIL; STOCK; ENERGY; PERFORMANCE; MANAGEMENT; DEMAND; PRICES; SYSTEM;
D O I
10.1016/j.eneco.2024.107885
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper examines the returns and volatilities connectedness between the electricity and AI-based markets using the Time-Varying Parameter Vector Autoregression (TVP-VAR) approach. Our sample covers the COVID-19 and Russia-Ukraine conflict-based sub-periods, and the time-varying results provide valuable insights into these two crisis episodes. Further, we estimate the determinants of returns and volatility spillovers between the electricity and AI stock markets. The following findings are apparent in our study: certain AI stocks are considered safer investments during high market risks and uncertainties; being the highest receiver of system shocks does not equate to the most vulnerability. The alternative electricity market acts as a net pairwise shock transmitter to the conventional electricity market; MSFT is the dominant asset in the system of network connectedness between the electricity and AI stock markets. Systemic and market risks and assets like Gold, Bitcoin, and BONDS significantly drive spillover interconnectedness between these electricity and artificial intelligence stock markets. These findings have implications for investors and policymakers.
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页数:16
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