Time and frequency connectedness among oil shocks, electricity and clean energy markets

被引：185

作者：

Naeem, Muhammad Abubakr ^{[1
]}

Peng, Zhe ^{[2
]}

Suleman, Mouhammed Tahir ^{[3
]}

Nepal, Rabindra ^{[4
]}

Shahzad, Syed Jawad Hussain ^{[5
,6
]}

机构：

[1] Massey Univ, Sch Econ & Finance, Auckland, New Zealand

[2] Wilfrid Laurier Univ, Lazaridis Sch Business & Econ, Waterloo, ON, Canada

[3] Univ Otago, Dept Accounting & Finance, Dunedin, New Zealand

[4] Univ Wollongong, Sch Accountancy Econ & Finance, Wollongong, NSW, Australia

[5] Montpellier Business Sch, Montpellier, France

[6] South Ural State Univ, Chelyabinsk, Russia

来源：

ENERGY ECONOMICS | 2020年 / 91卷

关键词：

Electricity market; Oil shocks; Carbon price; Clean energy; Time and frequency connectedness; IMPULSE-RESPONSE ANALYSIS; VOLATILITY SPILLOVERS; STOCK-PRICES; RENEWABLE ENERGY; CRUDE-OIL; CARBON; UNCERTAINTY; DEPENDENCE; RISK; TECHNOLOGY;

D O I：

10.1016/j.eneco.2020.104914

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper examines the time and frequency connectedness among electricity, carbon and clean energy markets, and oil price demand and supply shocks. In doing so, we use the spillover method proposed by Diebold and Yilmaz (2012) and its extension in the frequency domain by Barunik and Kfehlik (2018). We find increased connectedness during the global financial crisis as well as in the shale oil revolution period. The total connectedness is also higher in the short-run compared to the long-run. Due to their low connectedness, electricity futures can act as a risk diversifier and safe-haven asset against oil shocks. Net pairwise directional connectedness among oil shocks and the clean energy index is higher during the shale oil revolution. These results have important implications for investors with different investment time horizons. (C) 2020 Elsevier B.V. All rights reserved.

引用

页数：13

共 58 条

[1] Price determination in the EU ETS market: Theory and econometric analysis with market fundamentals
Aatola, Piia
Ollikainen, Markku
Toppinen, Anne
[J]. ENERGY ECONOMICS, 2013, 36 : 380 - 395
[2] On the dynamic dependence and investment performance of crude oil and clean energy stocks
Ahmad, Wasim
[J]. RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2017, 42 : 376 - 389
[3] Price drivers and structural breaks in European carbon prices 2005-2007
Alberola, Emilie
Chevallier, Julien
Cheze, Benoit
[J]. ENERGY POLICY, 2008, 36 (02) : 787 - 797
[4] Oil price uncertainty and the US stock market analysis based on a GARCH-in-mean VAR model
Alsalman, Zeina
[J]. ENERGY ECONOMICS, 2016, 59 : 251 - 260
[5] The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging
Badshah, Ihsan
Demirer, Riza
Suleman, Muhammad Tahir
[J]. ENERGY ECONOMICS, 2019, 84
[6] Spillover network of commodity uncertainties
Balli, Faruk
Naeem, Muhammad Abubakr
Shahzad, Syed Jawad Hussain
de Bruin, Anne
[J]. ENERGY ECONOMICS, 2019, 81 : 914 - 927
[7] Volatility spillovers in commodity markets: A large t-vector autoregressive approach
Barbaglia, Luca
Croux, Christophe
Wilms, Ines
[J]. ENERGY ECONOMICS, 2020, 85 (85)
[8] Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk
Barunik, Jozef
Krehlik, Tomas
[J]. JOURNAL OF FINANCIAL ECONOMETRICS, 2018, 16 (02) : 271 - 296
[9] Bhardwaj Geetesh., 2015, FACTS FANTASIES COMM
[10] Volatility Spillovers Arising from the Financialization of Commodities
Chan, Wing Hong
Shelton, Bryce
Wu, Yan Wendy
[J]. JOURNAL OF RISK AND FINANCIAL MANAGEMENT, 2018, 11 (04):

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