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Optimal hedging in the US natural gas market: The effect of maturity and cointegration

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  • Ghoddusi, Hamed
  • Emamzadehfard, Sahar

Abstract

We use the US natural gas market as the rich experimental context to test multiple features of hedging performances. First, we compare the hedging effectiveness of a single futures contract (i.e. Henry Hub) used for hedging six different physical price positions. Second, we examine the performance of hedging, when one uses a futures contract with time-to-maturity beyond the hedging horizon (i.e. a non-matching hedging strategy). Finally, we quantify the effect of accounting for cointegration and also the time varying volatility in the calculation of optimal hedge ratios. As a robustness check we conduct our analysis using both ex-ante (out of sample) and ex-post (in sample) methods. Our findings suggest that using longer maturity contracts may improve the hedging effectiveness. We also find that accounting for cointegration and time varying prices has minimal effect on the hedge ratio and hedging effectiveness for almost all physical prices. Our findings can inform businesses exposed to commodity price risks in on making better risk-management decisions.

Suggested Citation

  • Ghoddusi, Hamed & Emamzadehfard, Sahar, 2017. "Optimal hedging in the US natural gas market: The effect of maturity and cointegration," Energy Economics, Elsevier, vol. 63(C), pages 92-105.
  • Handle: RePEc:eee:eneeco:v:63:y:2017:i:c:p:92-105
    DOI: 10.1016/j.eneco.2017.01.018
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    2. Rama Malladi, 2022. "HARI: Characteristics of a new defined lifestyle (DL) retirement planning product," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 27(2), pages 147-163, June.
    3. Cuilin Li & Ya-Juan Du & Qiang Ji & Jiang-bo Geng, 2019. "Multiscale Market Integration and Nonlinear Granger Causality between Natural Gas Futures and Physical Markets," Sustainability, MDPI, vol. 11(19), pages 1-23, October.
    4. Zainudin, Ahmad Danial & Mohamad, Azhar, 2021. "Cross hedging with stock index futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 128-144.
    5. Panos K. Pouliasis & Ilias D. Visvikis & Nikos C. Papapostolou & Alexander A. Kryukov, 2020. "A novel risk management framework for natural gas markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 430-459, March.
    6. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    7. Luděk Benada, 2018. "Comparison of the Impact of Econometric Models on Hedging Performance by Crude Oil and Natural Gas," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 66(2), pages 423-429.
    8. George E. Halkos & Apostolos S. Tsirivis, 2019. "Energy Commodities: A Review of Optimal Hedging Strategies," Energies, MDPI, vol. 12(20), pages 1-19, October.
    9. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2023. "Natural gas and the utility sector nexus in the U.S.: Quantile connectedness and portfolio implications," Energy Economics, Elsevier, vol. 120(C).
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    More about this item

    Keywords

    Natural gas; Optimal hedging; Hedging effectiveness; Hedging with cointegrated series;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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