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Dynamic volatility spillover effects between wind and solar power generations: Implications for hedging strategies and a sustainable power sector

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  • Song, Feng
  • Cui, Jian
  • Yu, Yihua

Abstract

Large-scale wind and solar development is impeded severely by their inherent volatilities. This study applies a novel approach to reduce the renewable investment risks from the production perspective, although there are many related studies from the financial market perspective. Using daily data from the Gansu province of China between 2013 and 2018 based on a VAR-GARCH model, we first find that wind and solar power generation are volatile, negatively correlated, and exhibit strong time varying spillover effects. We then apply three different approaches to calculate the hedge ratios and optimal capacity portfolios of wind and solar in Gansu. The result from the best MVP approach shows that the optimal capacity weights are 28.3% for wind and 71.7% for solar. This study sheds light on designing a joint development strategy to reduce security risks and integration costs during transition toward a low carbon power sector.

Suggested Citation

  • Song, Feng & Cui, Jian & Yu, Yihua, 2022. "Dynamic volatility spillover effects between wind and solar power generations: Implications for hedging strategies and a sustainable power sector," Economic Modelling, Elsevier, vol. 116(C).
  • Handle: RePEc:eee:ecmode:v:116:y:2022:i:c:s0264999322002735
    DOI: 10.1016/j.econmod.2022.106036
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    as
    1. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    2. Bar-Lev, Dan & Katz, Steven, 1976. "A Portfolio Approach to Fossil Fuel Procurement in the Electric Utility Industry," Journal of Finance, American Finance Association, vol. 31(3), pages 933-947, June.
    3. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Gabauer, David & Dwumfour, Richard Adjei, 2022. "Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies," Global Finance Journal, Elsevier, vol. 51(C).
    6. Li, Mingquan & Virguez, Edgar & Shan, Rui & Tian, Jialin & Gao, Shuo & Patiño-Echeverri, Dalia, 2022. "High-resolution data shows China’s wind and solar energy resources are enough to support a 2050 decarbonized electricity system," Applied Energy, Elsevier, vol. 306(PA).
    7. Iglesias-Casal, Ana & López-Penabad, María-Celia & López-Andión, Carmen & Maside-Sanfiz, José Manuel, 2020. "Diversification and optimal hedges for socially responsible investment in Brazil," Economic Modelling, Elsevier, vol. 85(C), pages 106-118.
    8. Zhou, Wei & Gu, Qinen & Chen, Jin, 2021. "From volatility spillover to risk spread: An empirical study focuses on renewable energy markets," Renewable Energy, Elsevier, vol. 180(C), pages 329-342.
    9. Gunnar Luderer & Silvia Madeddu & Leon Merfort & Falko Ueckerdt & Michaja Pehl & Robert Pietzcker & Marianna Rottoli & Felix Schreyer & Nico Bauer & Lavinia Baumstark & Christoph Bertram & Alois Dirna, 2022. "Author Correction: Impact of declining renewable energy costs on electrification in low-emission scenarios," Nature Energy, Nature, vol. 7(4), pages 380-381, April.
    10. Fahmy, Hany, 2022. "Clean energy deserves to be an asset class: A volatility-reward analysis," Economic Modelling, Elsevier, vol. 106(C).
    11. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    12. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & de Gracia, Fernando Perez, 2020. "Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness," Energy Economics, Elsevier, vol. 91(C).
    13. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    14. Reboredo, Juan C. & Ugolini, Andrea, 2020. "Price connectedness between green bond and financial markets," Economic Modelling, Elsevier, vol. 88(C), pages 25-38.
    15. de Jong, P. & Sánchez, A.S. & Esquerre, K. & Kalid, R.A. & Torres, E.A., 2013. "Solar and wind energy production in relation to the electricity load curve and hydroelectricity in the northeast region of Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 526-535.
    16. Monforti, Fabio & Gonzalez-Aparicio, Iratxe, 2017. "Comparing the impact of uncertainties on technical and meteorological parameters in wind power time series modelling in the European Union," Applied Energy, Elsevier, vol. 206(C), pages 439-450.
    17. An, Henry & Qiu, Feng & Rude, James, 2021. "Volatility spillovers between food and fuel markets: Do administrative regulations affect the transmission?," Economic Modelling, Elsevier, vol. 102(C).
    18. Reboredo, Juan C., 2018. "Green bond and financial markets: Co-movement, diversification and price spillover effects," Energy Economics, Elsevier, vol. 74(C), pages 38-50.
    19. He, Gang & Kammen, Daniel M., 2014. "Where, when and how much wind is available? A provincial-scale wind resource assessment for China," Energy Policy, Elsevier, vol. 74(C), pages 116-122.
    20. Kang, Jia-Ning & Wei, Yi-Ming & Liu, Lan-Cui & Han, Rong & Yu, Bi-Ying & Wang, Jin-Wei, 2020. "Energy systems for climate change mitigation: A systematic review," Applied Energy, Elsevier, vol. 263(C).
    21. David C. Broadstock & Ioannis Chatziantoniou & David Gabauer, 2022. "Minimum Connectedness Portfolios and the Market for Green Bonds: Advocating Socially Responsible Investment (SRI) Activity," Springer Books, in: Christos Floros & Ioannis Chatziantoniou (ed.), Applications in Energy Finance, chapter 0, pages 217-253, Springer.
    22. Monforti, F. & Huld, T. & Bódis, K. & Vitali, L. & D'Isidoro, M. & Lacal-Arántegui, R., 2014. "Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach," Renewable Energy, Elsevier, vol. 63(C), pages 576-586.
    23. Mikovits, Christian & Wetterlund, Elisabeth & Wehrle, Sebastian & Baumgartner, Johann & Schmidt, Johannes, 2021. "Stronger together: Multi-annual variability of hydrogen production supported by wind power in Sweden," Applied Energy, Elsevier, vol. 282(PB).
    24. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    25. Christoffersen, Peter & Feunou, Bruno & Jacobs, Kris & Meddahi, Nour, 2014. "The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 663-697, June.
    26. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    27. Linh Pham, 2016. "Is it risky to go green? A volatility analysis of the green bond market," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 6(4), pages 263-291, October.
    28. Ávila R., Leandro & Mine, Miriam R.M. & Kaviski, Eloy & Detzel, Daniel H.M. & Fill, Heinz D. & Bessa, Marcelo R. & Pereira, Guilherme A.A., 2020. "Complementarity modeling of monthly streamflow and wind speed regimes based on a copula-entropy approach: A Brazilian case study," Applied Energy, Elsevier, vol. 259(C).
    29. Philip J. Heptonstall & Robert J. K. Gross, 2021. "A systematic review of the costs and impacts of integrating variable renewables into power grids," Nature Energy, Nature, vol. 6(1), pages 72-83, January.
    30. Gunnar Luderer & Silvia Madeddu & Leon Merfort & Falko Ueckerdt & Michaja Pehl & Robert Pietzcker & Marianna Rottoli & Felix Schreyer & Nico Bauer & Lavinia Baumstark & Christoph Bertram & Alois Dirna, 2022. "Impact of declining renewable energy costs on electrification in low-emission scenarios," Nature Energy, Nature, vol. 7(1), pages 32-42, January.
    31. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    32. Lion Hirth, 2013. "The Market Value of Variable Renewables. The Effect of Solar and Wind Power Variability on their Relative Price," RSCAS Working Papers 2013/36, European University Institute.
    33. Zhou, Sheng & Wang, Yu & Zhou, Yuyu & Clarke, Leon E. & Edmonds, James A., 2018. "Roles of wind and solar energy in China’s power sector: Implications of intermittency constraints," Applied Energy, Elsevier, vol. 213(C), pages 22-30.
    34. Tsuji, Chikashi, 2018. "Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses," Economic Modelling, Elsevier, vol. 74(C), pages 167-185.
    35. Christos Floros & Ioannis Chatziantoniou (ed.), 2022. "Applications in Energy Finance," Springer Books, Springer, number 978-3-030-92957-2, June.
    36. Zhang, Hengxu & Cao, Yongji & Zhang, Yi & Terzija, Vladimir, 2018. "Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data," Applied Energy, Elsevier, vol. 216(C), pages 172-182.
    37. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    38. Zhang, Bing & Wang, Peijie, 2014. "Return and volatility spillovers between china and world oil markets," Economic Modelling, Elsevier, vol. 42(C), pages 413-420.
    39. Zhang, Dayong & Zhang, Zhiwei & Managi, Shunsuke, 2019. "A bibliometric analysis on green finance: Current status, development, and future directions," Finance Research Letters, Elsevier, vol. 29(C), pages 425-430.
    40. Hirth, Lion, 2013. "The market value of variable renewables," Energy Economics, Elsevier, vol. 38(C), pages 218-236.
    41. Fernandes, Mário Correia & Dias, José Carlos & Nunes, João Pedro Vidal, 2021. "Modeling energy prices under energy transition: A novel stochastic-copula approach," Economic Modelling, Elsevier, vol. 105(C).
    42. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    43. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    44. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    45. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    46. Jin, Jiayu & Han, Liyan & Wu, Lei & Zeng, Hongchao, 2020. "The hedging effect of green bonds on carbon market risk," International Review of Financial Analysis, Elsevier, vol. 71(C).
    47. Thomas J. Fisher & Colin M. Gallagher, 2012. "New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 777-787, June.
    48. Hu, Haiqing & Chen, Di & Sui, Bo & Zhang, Lang & Wang, Yinyin, 2020. "Price volatility spillovers between supply chain and innovation of financial pledges in China," Economic Modelling, Elsevier, vol. 89(C), pages 397-413.
    49. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    Renewable energy; VAR-GARCH; Dynamic volatility spillovers; Hedging strategy; Sustainable economy;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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