IDEAS home Printed from https://ideas.repec.org/a/kap/rqfnac/v25y2005i2p125-137.html
   My bibliography  Save this article

Currency Hedging Using the Mean-Gini Framework

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11156-005-4245-9
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11156-005-4245-9?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Lien, Donald & Tse, Y K, 2002. "Some Recent Developments in Futures Hedging," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 357-396, July.
    8. 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.
    9. Jin, Zhezhen & Shao, Yongzhao, 1999. "On kernel estimation of a multivariate distribution function," Statistics & Probability Letters, Elsevier, vol. 41(2), pages 163-168, January.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    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. 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.

    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. Darren Butterworth & Phil Holmes, 2005. "The Hedging Effectiveness of U.K. Stock Index Futures Contracts Using an Extended Mean Gini Approach: Evidence for the FTSE 100 and FTSE Mid250 Contracts," Multinational Finance Journal, Multinational Finance Journal, vol. 9(3-4), pages 131-160, September.
    2. Rozaimah Zainudin & Roselee Shah Shaharudin, 2011. "Multi Mean Garch Approach to Evaluating Hedging Performance in the Crude Palm Oil Futures Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 7(1), pages 111-130.
    3. Dinica, Mihai Cristian & Armeanu, Daniel, 2014. "The Optimal Hedging Ratio for Non-Ferrous Metals," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 105-122, March.
    4. John Cotter & Jim Hanly, 2012. "Hedging effectiveness under conditions of asymmetry," The European Journal of Finance, Taylor & Francis Journals, vol. 18(2), pages 135-147, February.
    5. Jui-Cheng Hung & Chien-Liang Chiu & Ming-Chih Lee, 2006. "Hedging with zero-value at risk hedge ratio," Applied Financial Economics, Taylor & Francis Journals, vol. 16(3), pages 259-269.
    6. Lien, Donald & Yang, Li, 2008. "Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 187-198, February.
    7. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    8. Abdulnasser Hatemi-J & Eduardo Roca, 2006. "Calculating the optimal hedge ratio: constant, time varying and the Kalman Filter approach," Applied Economics Letters, Taylor & Francis Journals, vol. 13(5), pages 293-299.
    9. John Cotter & Jim Hanly, 2006. "Reevaluating hedging performance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(7), pages 677-702, July.
    10. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    11. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    12. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    13. Stavros Degiannakis & Christos Floros & Enrique Salvador & Dimitrios Vougas, 2022. "On the stationarity of futures hedge ratios," Operational Research, Springer, vol. 22(3), pages 2281-2303, July.
    14. Choudhry, Taufiq, 2009. "Short-run deviations and time-varying hedge ratios: Evidence from agricultural futures markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 58-65, March.
    15. Hou, Yang & Li, Steven, 2013. "Hedging performance of Chinese stock index futures: An empirical analysis using wavelet analysis and flexible bivariate GARCH approaches," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 109-131.
    16. Olson, Eric & Vivian, Andrew & Wohar, Mark E., 2019. "What is a better cross-hedge for energy: Equities or other commodities?," Global Finance Journal, Elsevier, vol. 42(C).
    17. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    18. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    19. Jebabli, Ikram & Roubaud, David, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Economic Modelling, Elsevier, vol. 70(C), pages 97-114.
    20. Chang, Chia-Lin & González-Serrano, Lydia & Jimenez-Martin, Juan-Angel, 2013. "Currency hedging strategies using dynamic multivariate GARCH," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 164-182.

    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:kap:rqfnac:v:25:y:2005:i:2:p:125-137. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://springer.com .

    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.