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A multi-factor model with time-varying and seasonal risk premiums for the natural gas market

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  • Shao, Chengwu
  • Bhar, Ramaprasad
  • Colwell, David B.

Abstract

In this paper, we develop a quantitative model of the US natural gas market that explores its multi-factor structure and its time-varying and seasonal risk premiums. With weekly spot and futures prices we show that three factors are preferred to describe the futures term structure, and the time-varying risk premiums are also significant. Moreover, we found that the market implies a seasonal risk premium with two peaks and troughs in one year, which is important to correctly price the futures by maturity month. Finally, we link this seasonal risk premium to the uncertainty of the US natural gas demand and find a positive relationship between them. These results reveal the complex aspect of the market, and may have useful applications for other commodity sectors.

Suggested Citation

  • Shao, Chengwu & Bhar, Ramaprasad & Colwell, David B., 2015. "A multi-factor model with time-varying and seasonal risk premiums for the natural gas market," Energy Economics, Elsevier, vol. 50(C), pages 207-214.
    • Handle: RePEc:eee:eneeco:v:50:y:2015:i:c:p:207-214
    DOI: 10.1016/j.eneco.2015.04.013
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    as
    1. J. Michael Harrison & Stanley R. Pliska, 1981. "Martingales and Stochastic Integrals in the Theory of Continous Trading," Discussion Papers 454, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    2. Cartea, Álvaro & Williams, Thomas, 2008. "UK gas markets: The market price of risk and applications to multiple interruptible supply contracts," Energy Economics, Elsevier, vol. 30(3), pages 829-846, May.
    3. Babbs, Simon H. & Nowman, K. Ben, 1999. "Kalman Filtering of Generalized Vasicek Term Structure Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 115-130, March.
    4. Hobæk Haff, Ingrid & Lindqvist, Ola & Løland, Anders, 2008. "Risk premium in the UK natural gas forward market," Energy Economics, Elsevier, vol. 30(5), pages 2420-2440, September.
    5. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    6. Cartea, Álvaro & Villaplana, Pablo, 2008. "Spot price modeling and the valuation of electricity forward contracts: The role of demand and capacity," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2502-2519, December.
    7. Svetlana Borovkova & Helyette Geman, 2006. "Seasonal and stochastic effects in commodity forward curves," Review of Derivatives Research, Springer, vol. 9(2), pages 167-186, September.
    8. Ramaprasad Bhar & Damien Lee, 2011. "Time‐varying market price of risk in the crude oil futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(8), pages 779-807, August.
    9. Na Jin & Sergio Lence & Chad Hart & Dermot Hayes, 2012. "The Long-Term Structure of Commodity Futures," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(3), pages 718-735.
    10. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, January.
    11. Chiou Wei, Song Zan & Zhu, Zhen, 2006. "Commodity convenience yield and risk premium determination: The case of the U.S. natural gas market," Energy Economics, Elsevier, vol. 28(4), pages 523-534, July.
    12. Timothy J. Considine & Donald F. Larson, 2001. "Risk premiums on inventory assets: the case of crude oil and natural gas," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(2), pages 109-126, February.
    13. Hendrik Bessembinder & Michael L. Lemmon, 2002. "Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets," Journal of Finance, American Finance Association, vol. 57(3), pages 1347-1382, June.
    14. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    15. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    16. Cheridito, Patrick & Filipovic, Damir & Kimmel, Robert L., 2007. "Market price of risk specifications for affine models: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 83(1), pages 123-170, January.
    17. 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.
    18. Harrison, J. Michael & Pliska, Stanley R., 1981. "Martingales and stochastic integrals in the theory of continuous trading," Stochastic Processes and their Applications, Elsevier, vol. 11(3), pages 215-260, August.
    19. Brennan, Michael J & Schwartz, Eduardo S, 1985. "Evaluating Natural Resource Investments," The Journal of Business, University of Chicago Press, vol. 58(2), pages 135-157, April.
    20. Jaime Casassus & Pierre Collin‐Dufresne, 2005. "Stochastic Convenience Yield Implied from Commodity Futures and Interest Rates," Journal of Finance, American Finance Association, vol. 60(5), pages 2283-2331, October.
    21. Gregory R. Duffee, 2002. "Term Premia and Interest Rate Forecasts in Affine Models," Journal of Finance, American Finance Association, vol. 57(1), pages 405-443, February.
    22. Villaplana Conde, Pablo, 2003. "Pricing power derivatives: a two-factor jump-diffusion approach," DEE - Working Papers. Business Economics. WB wb031805, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    23. 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.
    24. Mihaela Manoliu & Stathis Tompaidis, 2002. "Energy futures prices: term structure models with Kalman filter estimation," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 21-43.
    25. Mu, Xiaoyi, 2007. "Weather, storage, and natural gas price dynamics: Fundamentals and volatility," Energy Economics, Elsevier, vol. 29(1), pages 46-63, January.
    26. Gonzalo Cortazar & Lorenzo Naranjo, 2006. "An N‐factor Gaussian model of oil futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(3), pages 243-268, March.
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    Cited by:

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    2. Ewald, Christian & Zou, Yihan, 2021. "Analytic formulas for futures and options for a linear quadratic jump diffusion model with seasonal stochastic volatility and convenience yield: Do fish jump?," European Journal of Operational Research, Elsevier, vol. 294(2), pages 801-815.
    3. Zhang, Yue-Jun & Chen, Ming-Ying, 2018. "Evaluating the dynamic performance of energy portfolios: Empirical evidence from the DEA directional distance function," European Journal of Operational Research, Elsevier, vol. 269(1), pages 64-78.
    4. Wei Wei & Asger Lunde, 2020. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Monash Econometrics and Business Statistics Working Papers 10/20, Monash University, Department of Econometrics and Business Statistics.
    5. Rubaszek, Michał & Uddin, Gazi Salah, 2020. "The role of underground storage in the dynamics of the US natural gas market: A threshold model analysis," Energy Economics, Elsevier, vol. 87(C).
    6. Størdal, Ståle & Ewald, Christian-Oliver & Lien, Gudbrand & Haugom, Erik, 2023. "Trading time seasonality in electricity futures," Journal of Commodity Markets, Elsevier, vol. 31(C).
    7. Ewald, Christian-Oliver & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Wu, Yuexiang, 2022. "Trading time seasonality in commodity futures: An opportunity for arbitrage in the natural gas and crude oil markets?," Energy Economics, Elsevier, vol. 115(C).

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    More about this item

    Keywords

    Natural gas; Short-term and long-term factors; Risk premium; Seasonality;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • 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

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