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Measuring and Testing Natural Gas and Electricity Markets Volatility: Evidence from Alberta's Deregulated Markets

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  • Serletis Apostolos

    (University of Calgary)

  • Shahmoradi Akbar

    (RiskAdvisory Department, SAS Canada)

Abstract

In this paper we specify and estimate a multivariate GARCH-M model of natural gas and electricity price changes, and test for causal relationships between natural gas and electricity price changes and their volatilities, using data over the deregulated period from January 1, 1996 to November 9, 2004 from Alberta's (deregulated) spot power and natural gas markets. The model allows for the possibilities of spillovers and asymmetries in the variance-covariance structure for natural gas and electricity price changes, and also for the separate examination of the effects of the volatility of anticipated and unanticipated changes in natural gas and electricity prices.

Suggested Citation

  • Serletis Apostolos & Shahmoradi Akbar, 2006. "Measuring and Testing Natural Gas and Electricity Markets Volatility: Evidence from Alberta's Deregulated Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-20, September.
  • Handle: RePEc:bpj:sndecm:v:10:y:2006:i:3:n:10
    DOI: 10.2202/1558-3708.1341
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    1. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    2. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    3. Kalvinder Shields & Nilss Olekalns & Ãlan T. Henry & Chris Brooks, 2005. "Measuring the Response of Macroeconomic Uncertainty to Shocks," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 362-370, May.
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    Cited by:

    1. Serati, Massimiliano & Manera, Matteo & Plotegher, Michele, 2008. "Modeling Electricity Prices: From the State of the Art to a Draft of a New Proposal," International Energy Markets Working Papers 44426, Fondazione Eni Enrico Mattei (FEEM).
    2. Le Pen, Yannick & Sévi, Benoît, 2010. "Volatility transmission and volatility impulse response functions in European electricity forward markets," Energy Economics, Elsevier, vol. 32(4), pages 758-770, July.
    3. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.
    4. Balcilar, Mehmet & Hammoudeh, Shawkat & Toparli, Elif Akay, 2018. "On the risk spillover across the oil market, stock market, and the oil related CDS sectors: A volatility impulse response approach," Energy Economics, Elsevier, vol. 74(C), pages 813-827.
    5. Furió, Dolores & Chuliá, Helena, 2012. "Price and volatility dynamics between electricity and fuel costs: Some evidence for Spain," Energy Economics, Elsevier, vol. 34(6), pages 2058-2065.
    6. Xia, Tongshui & Ji, Qiang & Geng, Jiang-Bo, 2020. "Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    7. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    8. Olga Y. Uritskaya & Vadim M. Uritsky, 2015. "Predictability of price movements in deregulated electricity markets," Papers 1505.08117, arXiv.org.
    9. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 450-469, December.
    10. Mayis Gulali Gulaliyev & Gulshen Zahidqizi Yuzbashiyeva & Gulnara Vaqifqizi Mamedova & Samira Tahmazqizi Abasova & Fariz Rafiq Salahov & Ramil Ramiz Askerov, 2020. "Consumer Surplus Changing in the Transition from State Natural Monopoly to the Competitive Market in the Electricity Sector in the Developing Countries: Azerbaijan Case," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 265-275.
    11. Tadahiro Nakajima, 2019. "Expectations for Statistical Arbitrage in Energy Futures Markets," JRFM, MDPI, vol. 12(1), pages 1-12, January.
    12. Nakajima, Tadahiro & Hamori, Shigeyuki, 2013. "Testing causal relationships between wholesale electricity prices and primary energy prices," Energy Policy, Elsevier, vol. 62(C), pages 869-877.
    13. Schlueter, Stephan, 2010. "A long-term/short-term model for daily electricity prices with dynamic volatility," Energy Economics, Elsevier, vol. 32(5), pages 1074-1081, September.
    14. Moon, Jongwoo & Jung, Tae Yong, 2020. "A critical review of Korea's long-term contract for renewable energy auctions: The relationship between the import price of liquefied natural gas and system marginal price," Utilities Policy, Elsevier, vol. 67(C).
    15. Sapio, Alessandro & Spagnolo, Nicola, 2020. "The effect of a new power cable on energy prices volatility spillovers," Energy Policy, Elsevier, vol. 144(C).
    16. S. Vijayalakshmi & G. P. Girish, 2015. "Artificial Neural Networks for Spot Electricity Price Forecasting: A Review," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 1092-1097.
    17. Uritskaya, Olga Y. & Uritsky, Vadim M., 2015. "Predictability of price movements in deregulated electricity markets," Energy Economics, Elsevier, vol. 49(C), pages 72-81.
    18. Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
    19. Tiantian Liu & Xie He & Tadahiro Nakajima & Shigeyuki Hamori, 2020. "Influence of Fluctuations in Fossil Fuel Commodities on Electricity Markets: Evidence from Spot and Futures Markets in Europe," Energies, MDPI, vol. 13(8), pages 1-20, April.
    20. Chae, Yeoungjin & Kim, Myunghwan & Yoo, Seung-Hoon, 2012. "Does natural gas fuel price cause system marginal price, vice-versa, or neither? A causality analysis," Energy, Elsevier, vol. 47(1), pages 199-204.
    21. Serletis, Apostolos & Xu, Libo, 2016. "Volatility and a century of energy markets dynamics," Energy Economics, Elsevier, vol. 55(C), pages 1-9.
    22. Dolores Furio & Javier Poblacion, 2018. "Electricity and Natural Gas Prices Sharing the Long-term Trend: Some Evidence from the Spanish Market," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 173-180.

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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • N70 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - General, International, or Comparative
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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