IDEAS home Printed from https://ideas.repec.org/p/ags/nccc11/285352.html

The Role of Long Memory in Hedging Strategies for Canadian Commodity Futures

Author

Listed:
  • Mann, Janelle

Abstract

This research paper investigates whether ICE futures contracts are an effective and affordable strategy to manage price risk for Canadian commodity producers in recent periods of high price volatility. Long memory in volatility is found to be present in cash and futures prices for canola and western barley. This finding is incorporated into the hedging strategy by estimating hedge ratios using a FIAPARCH model. Findings indicate that the ICE futures contracts for canola is an effective and affordable means of reducing price risk for canola producers and should be considered as part of a price risk management strategy. On the other hand, the findings indicate that the ICE futures contract for western barley is not as effective as a means of reducing price risk for western barley producers; however, it is affordable. At the current time, western barley producers should consider alternative means of price risk management; however, the ICE futures contract should be reconsidered after modifications to contract specifications come into effect.

Suggested Citation

  • Mann, Janelle, 2011. "The Role of Long Memory in Hedging Strategies for Canadian Commodity Futures," 2011 Conference, April 18-19, 2011, St. Louis, Missouri 285352, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:nccc11:285352
    DOI: 10.22004/ag.econ.285352
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/285352/files/confp23-11.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.285352?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    2. Paul Brockman & Yiuman Tse, 1995. "Information shares in Canadian agricultural cash and futures markets," Applied Economics Letters, Taylor & Francis Journals, vol. 2(10), pages 335-338.
    3. Jian Yang & David A. Bessler & David J. Leatham, 2001. "Asset storability and price discovery in commodity futures markets: A new look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 279-300, March.
    4. Brunetti, Celso & Gilbert, Christopher L., 2000. "Bivariate FIGARCH and fractional cointegration," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 509-530, December.
    5. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    6. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    7. Jian Yang & Titus Awokuse, 2003. "Asset storability and hedging effectiveness in commodity futures markets," Applied Economics Letters, Taylor & Francis Journals, vol. 10(8), pages 487-491.
    8. Donald Lien & Y. K. Tse & Albert Tsui, 2002. "Evaluating the hedging performance of the constant-correlation GARCH model," Applied Financial Economics, Taylor & Francis Journals, vol. 12(11), pages 791-798.
    9. Hector O. Zapata & T. Randall Fortenbery, 1996. "Stochastic Interest Rates and Price Discovery in Selected Commodity Markets," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 18(4), pages 643-654.
    10. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    11. David A. Bessler & Ted Covey, 1991. "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(4), pages 461-474, August.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Hyun J. Jin & Darren L. Frechette, 2004. "Fractional Integration in Agricultural Futures Price Volatilities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 432-443.
    14. Peter S. Sephton, 1998. "GARCH and MARKOV Hedging at the Winnipeg Commodity Exchange," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 46(2), pages 117-126, July.
    15. Nuno Crato & Bonnie K. Ray, 2000. "Memory in returns and volatilities of futures' contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(6), pages 525-543, July.
    16. Coakley, Jerry & Dollery, Jian & Kellard, Neil, 2008. "The role of long memory in hedging effectiveness," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3075-3082, February.
    17. Carrion-i-Silvestre, Josep Lluis & Sanso-i-Rossello, Andreu & Ortuno, Manuel Artis, 2001. "Unit root and stationarity tests' wedding," Economics Letters, Elsevier, vol. 70(1), pages 1-8, January.
    18. Isabel Figuerola‐Ferretti & Christopher L. Gilbert, 2008. "Commonality in the LME aluminum and copper volatility processes through a FIGARCH lens," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(10), pages 935-962, October.
    19. Peter S. Sephton, 1993. "Optimal Hedge Ratios at the Winnipeg Commodity Exchange," Canadian Journal of Economics, Canadian Economics Association, vol. 26(1), pages 175-193, February.
    20. Peter S. Sephton, 2009. "Fractional integration in agricultural futures price volatilities revisited," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 103-111, January.
    21. Ted C. Schroeder & Barry K. Goodwin, 1991. "Price discovery and cointegration for live hogs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(6), pages 685-696, December.
    22. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    23. Y. K. Tse, 1998. "The conditional heteroscedasticity of the yen-dollar exchange rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-55.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Naveen Musunuru, 2019. "Modeling Long Range Dependence in Wheat Food Price Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(9), pages 1-46, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. CHIA-LIN CHANG & MICHAEL McALEER & ROENGCHAI TANSUCHAT, 2012. "Modelling Long Memory Volatility In Agricultural Commodity Futures Returns," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-27.
    2. Heni Boubaker & Bassem Saidane & Mouna Ben Saad Zorgati, 2022. "Modelling the dynamics of stock market in the gulf cooperation council countries: evidence on persistence to shocks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.
    3. Jonathan Dark, 2004. "Long term hedging of the Australian All Ordinaries Index using a bivariate error correction FIGARCH model," Monash Econometrics and Business Statistics Working Papers 7/04, Monash University, Department of Econometrics and Business Statistics.
    4. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
    5. Mann, Janelle & Sephton, Peter, 2010. "A Comparison of Hedging Strategies and Effectiveness for Storable and Non-Storable Commodities," 2010 Conference, April 19-20, 2010, St. Louis, Missouri 285325, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    6. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    7. Geoffrey Ngene & Ann Nduati Mungai & Allen K. Lynch, 2018. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, June.
    8. Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics in Foreign Exchange Rates : Further Evidence from the Malaysian Ringgit and Singapore Dollar," Finance Working Papers 22571, East Asian Bureau of Economic Research.
    9. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    10. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Energy Policy, Elsevier, vol. 69(C), pages 227-247.
    11. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2023. "A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1801-1843, December.
    12. Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.
    13. Bozic, Marin & Fortenbery, T. Randall, 2012. "Price Discovery, Volatility Spillovers and Adequacy of Speculation," 2012 Conference, April 16-17, 2012, St. Louis, Missouri 285784, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    14. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    15. Xu, Xiaojie, 2014. "Price Discovery in U.S. Corn Cash and Futures Markets: The Role of Cash Market Selection," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169809, Agricultural and Applied Economics Association.
    16. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    17. González-Pla, Francisco & Lovreta, Lidija, 2019. "Persistence in firm’s asset and equity volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    18. Stavros Stavroyiannis & Leonidas Zarangas, 2013. "Out of Sample Value-at-Risk and Backtesting with the Standardized Pearson Type-IV Skewed Distribution," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 60(2), pages 231-247, April.
    19. Timotheos Angelidis & Stavros Degiannakis, . "Backtesting VaR models:a two-stage procedure," Journal of Risk Model Validation, Journal of Risk Model Validation.
    20. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised 04 Mar 2003.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:nccc11:285352. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: http://www.farmdoc.illinois.edu/nccc134/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.