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Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives

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  • Guo, Zi-Yi

Abstract

We adopt Schwartz and Smith’s model (2000) to calculate risk measures of Brent oil futures contracts and light sweet crude oil (WTI) futures contracts and Mirantes, Poblacion and Serna’s model (2012) to calculate risk measures of natural gas futures contracts, gasoil futures contracts, heating oil futures contracts, RBOB gasoline futures contracts, PJM western hub peak and off-peak electricity futures contracts. We show that the models present well goodness of fit and explain two stylized facts of the data: the Samuelson effect and the seasonality effect. Our backtesting results demonstrate that the models provide satisfactory risk measures for listed energy commodity futures contracts. A simple estimation method possessing quick convergence is developed.

Suggested Citation

  • Guo, Zi-Yi, 2017. "Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives," EconStor Preprints 167619, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:167619
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    2. James S. Doran & Ehud I. Ronn, 2021. "Hedging Long-Dated Oil Futures and Options Using Short-Dated Securities—Revisiting Metallgesellschaft," JRFM, MDPI, vol. 14(8), pages 1-10, August.
    3. Yoon Hong & Ji-chul Lee & Guoping Ding, 2017. "Volatility Clustering, New Heavy-Tailed Distribution and the Stock Market Returns in South Korea," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 6(3), pages 164-169, September.
    4. Guo, Zi-Yi, 2017. "Martingale Regressions for a Continuous Time Model of Exchange Rates," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(2), pages 40-45.

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    Keywords

    Samuelson effect; seasonal effect; value-at-risk; least-square-estimation;
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