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
论文数: 0引用数: 0
h-index: 0
机构:
Prince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
Univ Jordan, Sch Business, Amman, JordanPrince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
Yousaf, Imran
[1
,2
]
Ohikhuare, Obaika M.
论文数: 0引用数: 0
h-index: 0
机构:
Fed Univ Agr, Dept Econ, Abeokuta, Ogun State, NigeriaPrince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
Ohikhuare, Obaika M.
[3
]
Li, Yong
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Normal Univ, Tianhua Coll, Shanghai, Peoples R ChinaPrince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
Li, Yong
[4
]
Li, Yanshuang
论文数: 0引用数: 0
h-index: 0
机构:
Dongbei Univ Finance & Econ, Sch Fintech, Dalian, Peoples R ChinaPrince Sultan Univ, Coll Business Adm, Dept Finance, Riyadh, Saudi Arabia
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
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.
机构:
Univ Sfax, Inst Higher Business Studies Sfax, Res Lab Probabil & Stat, Sfax, TunisiaUniv Sfax, Inst Higher Business Studies Sfax, Res Lab Probabil & Stat, Sfax, Tunisia
Mroua, Mourad
Bouattour, Hejer
论文数: 0引用数: 0
h-index: 0
机构:
Univ Sfax, Fac Econ & Management, Res Lab Probabil & Stat, Sfax, TunisiaUniv Sfax, Inst Higher Business Studies Sfax, Res Lab Probabil & Stat, Sfax, Tunisia
机构:
Wenzhou Kean Univ, Coll Business & Publ Management, Wenzhou, Peoples R ChinaWenzhou Kean Univ, Coll Business & Publ Management, Wenzhou, Peoples R China
Yousaf, Imran
Pham, Linh
论文数: 0引用数: 0
h-index: 0
机构:
Lake Forest Coll, Lake Forest, IL USAWenzhou Kean Univ, Coll Business & Publ Management, Wenzhou, Peoples R China
Pham, Linh
Goodell, John W.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Akron, Coll Business, Akron, OH 44325 USAWenzhou Kean Univ, Coll Business & Publ Management, Wenzhou, Peoples R China