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Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach

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  • Moschini, GianCarlo
  • Myers, Robert J.

Abstract

The authors develop a new multivariate GARCH parameterization that is suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity. The advantage of the new parameterization is that it allows for a flexible form of time-varying volatility, even under the null of a constant hedge ratio. The model is estimated using weekly corn prices. Statistical tests reject the null hypothesis of a constant hedge ratio and also reject the null that time variation in optimal hedge ratios can be explained solely by deterministic seasonality and time-to-maturity effects.
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Suggested Citation

  • Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
  • Handle: RePEc:eee:empfin:v:9:y:2002:i:5:p:589-603
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    1. Moschini, Giancarlo & Lapan, Harvey, 1995. "The Hedging Role of Options and Futures under Joint Price, Basis, and Production Risk," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(4), pages 1025-1049, November.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Cecchetti, Stephen G & Cumby, Robert E & Figlewski, Stephen, 1988. "Estimation of the Optimal Futures Hedge," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 623-630, November.
    4. Lence, Sergio H., 1995. "On the optimal hedge under unbiased futures prices," Economics Letters, Elsevier, vol. 47(3-4), pages 385-388, March.
    5. Moschini, Giancarlo & Hennessy, David A., 2001. "Uncertainty, risk aversion, and risk management for agricultural producers," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 2, pages 88-153, Elsevier.
    6. Harvey Lapan & Giancarlo Moschini & Steven D. Hanson, 1991. "Production, Hedging, and Speculative Decisions with Options and Futures Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(1), pages 66-74.
    7. 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.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Ronald W. Anderson & Jean-Pierre Danthine, 1983. "The Time Pattern of Hedging and the Volatility of Futures Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(2), pages 249-266.
    10. Karp, Larry S, 1988. "Dynamic Hedging with Uncertain Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(4), pages 621-637, November.
    11. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    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.
    13. Robert J. Myers & Stanley R. Thompson, 1989. "Generalized Optimal Hedge Ratio Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 858-868.
    14. Benninga, Simon & Eldor, Rafael & Zilcha, Itzhak, 1983. "Optimal hedging in the futures market under price uncertainty," Economics Letters, Elsevier, vol. 13(2-3), pages 141-145.
    15. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    16. Lumsdaine, Robin L, 1996. "Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models," Econometrica, Econometric Society, vol. 64(3), pages 575-596, May.
    17. repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
    18. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    19. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March.
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