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Hedging effectiveness under conditions of asymmetry

Author

Listed:
  • John Cotter
  • Jim Hanly

Abstract

We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail-specific metrics, for example, value at risk, to compare the hedging effectiveness of short and long hedgers. Comparisons are applied to a number of hedging strategies including OLS and both symmetric and asymmetric generalised autoregressive conditional heteroskedastic models. We apply our analysis to a dataset consisting of S&P500 index cash and futures containing symmetric and asymmetric return distributions chosen ex post . Our findings show that asymmetry reduces out-of-sample hedging performance and that significant differences occur in hedging performance between short and long hedgers.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:eurjfi:v:18:y:2012:i:2:p:135-147
    DOI: 10.1080/1351847X.2011.574977
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    Cited by:

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    3. Wei-Han Liu, 2014. "Optimal hedge ratio estimation and hedge effectiveness with multivariate skew distributions," Applied Economics, Taylor & Francis Journals, vol. 46(12), pages 1420-1435, April.
    4. Xiong, Youlin & Shen, Jun & Yoon, Seong-Min & Dong, Xiyong, 2024. "Macroeconomic determinants of the long-term correlation between stock and exchange rate markets in China: A DCC-MIDAS-X approach considering structural breaks," Finance Research Letters, Elsevier, vol. 61(C).
    5. Lerskullawat, Polwat, 2019. "Hedging Effectiveness on the Thailand Futures Exchange Market," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(2), December.
    6. Zhang, Hongwei & Wei, Shiyao & Guo, Yaoqi, 2025. "Long-term correlation between the green and conventional bond markets: The roles of categorical EPU indices and structural changes," Research in International Business and Finance, Elsevier, vol. 77(PA).
    7. 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.
    8. Bessler, Wolfgang & Wolff, Dominik, 2014. "Hedging European government bond portfolios during the recent sovereign debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 379-399.
    9. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    10. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2021. "How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Deepika Krishnan, 2023. "Hedging With Futures: Contract in the Indian Stock Market," International Journal of Applied Behavioral Economics (IJABE), IGI Global Scientific Publishing, vol. 12(1), pages 1-18, January.
    12. Chuang, Chung-Chu & Wang, Yi-Hsien & Yeh, Tsai-Jung & Chuang, Shuo-Li, 2014. "Backtesting VaR in consideration of the higher moments of the distribution for minimum-variance hedging portfolios," Economic Modelling, Elsevier, vol. 42(C), pages 15-19.
    13. Yu‐Sheng Lai, 2022. "Use of high‐frequency data to evaluate the performance of dynamic hedging strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 104-124, January.
    14. Aleksander Olstad & George Filis & Stavros Degiannakis, 2021. "Oil and currency volatilities: Co‐movements and hedging opportunities," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2351-2374, April.
    15. Jing-Yi Lai, 2012. "An empirical study of the impact of skewness and kurtosis on hedging decisions," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1827-1837, December.
    16. 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.
    17. Luděk Benada, 2018. "Comparison of the Impact of Econometric Models on Hedging Performance by Crude Oil and Natural Gas," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 66(2), pages 423-429.
    18. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2020. "Asymmetric dependence structures for regional stock markets: An unconditional quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    19. Dong, Xiyong & Xiong, Youlin & Nie, Siyue & Yoon, Seong-Min, 2023. "Can bonds hedge stock market risks? Green bonds vs conventional bonds," Finance Research Letters, Elsevier, vol. 52(C).
    20. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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