Are clean energy markets hedges for stock markets? A tail quantile connectedness regression

被引:12
作者
Ziadat, Salem Adel [1 ,2 ]
Mensi, Walid [4 ,6 ]
Al-Kharusi, Sami [3 ]
Vo, Xuan Vinh [3 ,4 ,5 ]
Kang, Sang Hoon [7 ]
机构
[1] Al Ahliyya Amman Univ, Fac Business, Amman, Jordan
[2] Univ Ottawa, Telfer Sch Management, Ottawa, ON, Canada
[3] Sultan Qaboos Univ, Coll Econ & Polit Sci, Dept Econ & Finance, Muscat, Oman
[4] Univ Econ Ho Chi Minh City, Inst Business Res, Ho Chi Minh, Vietnam
[5] Univ Econ Ho Chi Minh City, CFVG, Ho Chi Minh, Vietnam
[6] Muscat Univ, Muscat, Oman
[7] Pusan Natl Univ, Sch Business, Jangjeon 2 Dong, Busan 609735, South Korea
基金
新加坡国家研究基金会;
关键词
Clean energy; Stocks; Spillover; Portfolio management; IMPULSE-RESPONSE ANALYSIS; FINANCIAL-MARKETS; VOLATILITY SPILLOVERS; CO-MOVEMENT; OIL PRICES;
D O I
10.1016/j.eneco.2024.107757
中图分类号
F [经济];
学科分类号
02 ;
摘要
Acknowledging the long-term potential of alternative energy sources, this paper examines the quantile frequency connectedness between clean energy markets and international stock markets, with implications related to hedging effectiveness. The main results point out that spillovers run from the US, the EU, the UK, and the Renewable Energy and Clean Technology Index to Japan and the Global Clean Energy Index. Furthermore, while the transmissions are concentrated in the short run during normal (0.5) and bull market (0.95) conditions, they extend to intermediate and long-term amid busting market (0,05 quantile) states, signifying a long-lasting impact that cannot be absorbed in the short run. Notably, clean energy index roles in information transmissions range from a net sender (Renewable Energy and Clean Technology Index), isolated (Green Bond Index), and a net receiver (Global Clean Energy Index). From a multivariant portfolio design perspective, we notice that a substantial weight should be allocated to clean energy assets, WTI, and CSI300 when compared with the rest of the financial markets. Moreover, the low (high) volatility regime yields lower (higher) weights than the ones reported in the mean state, but the results remain largely similar. Bivariant portfolio weights show that GB should have substantial weight when paired with all assets.
引用
收藏
页数:24
相关论文
共 63 条
[1]   Optimal hedge ratios for clean energy equities [J].
Ahmad, Wasim ;
Sadorsky, Perry ;
Sharma, Amit .
ECONOMIC MODELLING, 2018, 72 :278-295
[2]   Cryptocurrencies and stock market indices. Are they related? [J].
Alberiko Gil-Alana, Luis ;
Abakah, Emmanuel Joel Aikins ;
Romero Rojo, Maria Fatima .
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2020, 51
[3]   Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management [J].
Alomari, Mohammad ;
Mensi, Walid ;
Vo, Xuan Vinh ;
Kang, Sang Hoon .
RESOURCES POLICY, 2022, 79
[4]   Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks [J].
Ando, Tomohiro ;
Greenwood-Nimmo, Matthew ;
Shin, Yongcheol .
MANAGEMENT SCIENCE, 2022, 68 (04) :2401-2431
[5]   A new approach to measuring financial contagion [J].
Bae, KH ;
Karolyi, GA ;
Stulz, RM .
REVIEW OF FINANCIAL STUDIES, 2003, 16 (03) :717-763
[6]   The Unprecedented Stock Market Reaction to COVID-19 [J].
Baker, Scott R. ;
Bloom, Nicholas ;
Davis, Steven J. ;
Kost, Kyle ;
Sammon, Marco ;
Viratyosin, Tasaneeya .
REVIEW OF ASSET PRICING STUDIES, 2020, 10 (04) :742-758
[7]   Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk [J].
Barunik, Jozef ;
Krehlik, Tomas .
JOURNAL OF FINANCIAL ECONOMETRICS, 2018, 16 (02) :271-296
[8]   International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks [J].
Bondia, Ripsy ;
Ghosh, Sajal ;
Kanjilal, Kakali .
ENERGY, 2016, 101 :558-565
[9]  
Bouri E., 2017, Renew. Sust. Energ. Rev, V69, P1366
[10]  
Broadstock D. C., 2022, Applications in Energy Finance, P217, DOI [10.1007/978-3-030-92957-2_9, DOI 10.1007/978-3-030-92957-2_9]