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Hedging downside risk with futures contracts

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  • Donald Lien
  • Yiu Kuen Tse
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    Abstract

    This paper considers a futures hedge strategy that minimizes the lower partial moments; such a strategy minimizes the downside risk and is consistent with the expected utility hypothesis. Two statistical methods are adopted to estimate the optimal hedge ratios: the empirical distribution function method and the kernel density estimation method. Both methods are applied to the Nikkei Stock Average (NSA) spot and futures markets. It is found that, for a hedger who is willing to absorb small losses but otherwise extremely cautious about large losses, the optimal hedge strategy that minimizes the lower partial moments may be sharply different from the minimum variance hedge strategy. If a hedger cares for downside-only risk, then the conventional minimum variance hedge strategy is inappropriate. The methods presented in this paper will be useful in these scenarios.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/096031000331798
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

    Volume (Year): 10 (2000)
    Issue (Month): 2 ()
    Pages: 163-170

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    Handle: RePEc:taf:apfiec:v:10:y:2000:i:2:p:163-170

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    Cited by:
    1. Cifarelli, Giulio & Paladino, Giovanna, 2011. "Hedging vs. speculative pressures on commodity futures returns," MPRA Paper 28229, University Library of Munich, Germany.
    2. Jonathan Dark, 2005. "A Critique of Minimum Variance Hedging," Accounting Research Journal, Emerald Group Publishing, vol. 18(1), pages 40-49, June.
    3. Chen, Sheng-Syan & Lee, Cheng-few & Shrestha, Keshab, 2008. "Do the pure martingale and joint normality hypotheses hold for futures contracts: Implications for the optimal hedge ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(1), pages 153-174, February.
    4. Demirer, Riza & Lien, Donald, 2003. "Downside risk for short and long hedgers," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 25-44.
    5. 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.
    6. Ahmedov, Zafarbek & Woodard, Joshua D., 2012. "Do RIN Mandates and Blender's Tax Credit Affect Blenders' Hedging Strategies?," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124980, Agricultural and Applied Economics Association.
    7. 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.
    8. Liu, Xiaochun & Jacobsen, Brian, 2011. "The Dynamic International Optimal Hedge Ratio," MPRA Paper 35260, University Library of Munich, Germany.
    9. Mattos, Fabio & Garcia, Philip & Nelson, Carl, 2008. "Relaxing standard hedging assumptions in the presence of downside risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(1), pages 78-93, February.
    10. 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.
    11. Chen, Sheng-Syan & Lee, Cheng-few & Shrestha, Keshab, 2003. "Futures hedge ratios: a review," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 433-465.
    12. Lien, Donald & Tse, Yiu Kuen, 2001. "Hedging downside risk: futures vs. options," International Review of Economics & Finance, Elsevier, vol. 10(2), pages 159-169.
    13. Hilal, Sawsan & Poon, Ser-Huang & Tawn, Jonathan, 2011. "Hedging the black swan: Conditional heteroskedasticity and tail dependence in S&P500 and VIX," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2374-2387, September.
    14. Fu, Junhui, 2014. "Multi-objective hedging model with the third central moment and the capital budget," Economic Modelling, Elsevier, vol. 36(C), pages 213-219.

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