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Currency Hedging Using the Mean-Gini Framework

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  • David Shaffer
  • Andrea DeMaskey

Abstract

The mean-Gini framework has been suggested as a robust alternative to the portfolio approach to futures hedging given its optimality under general distributional conditions. However, calculation of the Gini hedge ratio requires estimation of the underlying price distribution. We estimate minimum-Gini hedge ratios using two widely-used estimation procedures, the empirical distribution function method and the kernel method, for three emerging market and three developed market currencies. We find that these methods yield different Gini hedge ratios. These differences increase with risk aversion and are statistically significant for all developed market currencies but only one emerging market currency. In-sample analyses show that the empirical distribution function method is more effective at risk reduction than the kernel method for developed market currencies, whereas the kernel method is superior for emerging market currencies. Post-sample analyses strengthen the superiority of the empirical distribution function method for developed market and, in several cases, for emerging market currencies. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • David Shaffer & Andrea DeMaskey, 2005. "Currency Hedging Using the Mean-Gini Framework," Review of Quantitative Finance and Accounting, Springer, vol. 25(2), pages 125-137, September.
    • Handle: RePEc:kap:rqfnac:v:25:y:2005:i:2:p:125-137
    DOI: 10.1007/s11156-005-4245-9
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    References listed on IDEAS

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    1. Donald Lien & Yiu Kuen Tse, 2000. "Hedging downside risk with futures contracts," Applied Financial Economics, Taylor & Francis Journals, vol. 10(2), pages 163-170.
    2. 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.
    3. 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.
    4. Jin, Zhezhen & Shao, Yongzhao, 1999. "On kernel estimation of a multivariate distribution function," Statistics & Probability Letters, Elsevier, vol. 41(2), pages 163-168, January.
    5. Yitzhaki, Shlomo, 1982. "Stochastic Dominance, Mean Variance, and Gini's Mean Difference," American Economic Review, American Economic Association, vol. 72(1), pages 178-185, March.
    6. 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.
    7. Ah-Boon Sim & Ralf Zurbruegg, 2001. "Optimal hedge ratios and alternative hedging strategies in the presence of cointegrated time-varying risks," The European Journal of Finance, Taylor & Francis Journals, vol. 7(3), pages 269-283.
    8. Ghosh, Asim, 1995. "The Hedging Effectiveness of ECU Futures Contracts: Forecasting Evidence from an Error Correction Model," The Financial Review, Eastern Finance Association, vol. 30(3), pages 567-581, August.
    9. Shalit, Haim & Yitzhaki, Shlomo, 1984. "Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets," Journal of Finance, American Finance Association, vol. 39(5), pages 1449-1468, December.
    10. Wilkinson, Katherine J & Rose, Lawrence C & Young, Martin R, 1999. "Comparing the Effectiveness of Traditional and Time Varying Hedge Ratios Using New Zealand and Australian Debt Futures Contracts," The Financial Review, Eastern Finance Association, vol. 34(3), pages 79-94, August.
    11. Yitzhaki, Shlomo, 1983. "On an Extension of the Gini Inequality Index," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 617-628, October.
    12. Shao, Yongzhao & Xiang, Xiaojing, 1997. "Some extensions of the asymptotics of a kernel estimator of a distribution function," Statistics & Probability Letters, Elsevier, vol. 34(3), pages 301-308, June.
    13. repec:bla:jecsur:v:16:y:2002:i:3:p:357-96 is not listed on IDEAS
    14. Lerman, Robert I. & Yitzhaki, Shlomo, 1984. "A note on the calculation and interpretation of the Gini index," Economics Letters, Elsevier, vol. 15(3-4), pages 363-368.
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    Cited by:

    1. Dean Leistikow & Ren-Raw Chen, 2019. "Carry Cost Rate Regimes and Futures Hedge Ratio Variation," JRFM, MDPI, vol. 12(2), pages 1-17, May.
    2. Lutz Hahnenstein & Klaus Röder, 2007. "Who hedges more when leverage is endogenous? A testable theory of corporate risk management under general distributional conditions," Review of Quantitative Finance and Accounting, Springer, vol. 28(4), pages 353-391, May.
    3. Dean Leistikow & Ren-Raw Chen & Yuewu Xu, 2022. "Spot asset carry cost rates and futures hedge ratios," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1741-1779, May.

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