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A supply and demand based volatility model for energy prices

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  • Kanamura, Takashi

Abstract

This paper proposes a new volatility model for energy prices using the supply-demand relationship, which we call a supply and demand based volatility model. We show that the supply curve shape in the model determines the characteristics of the volatility in energy prices. It is found that the inverse Box-Cox transformation supply curve reflecting energy markets causes the inverse leverage effect, i.e., positive correlation between energy prices and volatility. The model is also used to show that an existing (G)ARCH-M model has the foundations on the supply-demand relationship. Additionally, we conduct the empirical studies analyzing the volatility in the U.S. natural gas prices.

Suggested Citation

  • Kanamura, Takashi, 2009. "A supply and demand based volatility model for energy prices," Energy Economics, Elsevier, vol. 31(5), pages 736-747, September.
  • Handle: RePEc:eee:eneeco:v:31:y:2009:i:5:p:736-747
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    1. Emanuel, David C. & MacBeth, James D., 1982. "Further Results on the Constant Elasticity of Variance Call Option Pricing Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(4), pages 533-554, November.
    2. Pirrong, Craig & Jermakyan, Martin, 2008. "The price of power: The valuation of power and weather derivatives," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2520-2529, December.
    3. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    4. Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July.
    5. M. T. Barlow, 2002. "A Diffusion Model For Electricity Prices," Mathematical Finance, Wiley Blackwell, vol. 12(4), pages 287-298, October.
    6. Gibson, Rajna & Schwartz, Eduardo S, 1990. "Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Richard Deaves & Itzhak Krinsky, 1992. "Risk Premiums and Efficiency in the Market for Crude Oil Futures," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 93-118.
    9. Kanamura, Takashi & Ohashi, Kazuhiko, 2007. "A structural model for electricity prices with spikes: Measurement of spike risk and optimal policies for hydropower plant operation," Energy Economics, Elsevier, vol. 29(5), pages 1010-1032, September.
    10. Kolos, Sergey P. & Ronn, Ehud I., 2008. "Estimating the commodity market price of risk for energy prices," Energy Economics, Elsevier, vol. 30(2), pages 621-641, March.
    11. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    12. 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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    7. Sun, Mei & Wang, Xiaofang & Chen, Ying & Tian, Lixin, 2011. "Energy resources demand-supply system analysis and empirical research based on non-linear approach," Energy, Elsevier, vol. 36(9), pages 5460-5465.
    8. Wang, Xiaofei & Liu, Chuangeng & Chen, Shaojie & Chen, Lei & Li, Ke & Liu, Na, 2020. "Impact of coal sector’s de-capacity policy on coal price," Applied Energy, Elsevier, vol. 265(C).
    9. Ding, Ashley, 2021. "A state-preference volatility index for the natural gas market," Energy Economics, Elsevier, vol. 104(C).
    10. Nomikos, Nikos & Andriosopoulos, Kostas, 2012. "Modelling energy spot prices: Empirical evidence from NYMEX," Energy Economics, Elsevier, vol. 34(4), pages 1153-1169.
    11. Andrea Petrella & Sandro Sapio, 2010. "No PUN intended: A time series analysis of the Italian day-ahead electricity prices," RSCAS Working Papers 2010/03, European University Institute.
    12. Sharma, Susan Sunila, 2010. "The relationship between energy and economic growth: Empirical evidence from 66 countries," Applied Energy, Elsevier, vol. 87(11), pages 3565-3574, November.
    13. Xiaopeng Guo & Jiaxing Shi & Dongfang Ren, 2016. "Coal Price Forecasting and Structural Analysis in China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-7, October.
    14. Samet Gunay & Audil Rashid Khaki, 2018. "Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models," JRFM, MDPI, vol. 11(2), pages 1-19, June.
    15. Kanamura, Takashi, 2016. "Role of carbon swap trading and energy prices in price correlations and volatilities between carbon markets," Energy Economics, Elsevier, vol. 54(C), pages 204-212.
    16. Sun, Mei & Wang, Yaqi & Gao, Cuixia, 2016. "Visibility graph network analysis of natural gas price: The case of North American market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1-11.
    17. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
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