IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v466y2017icp502-510.html
   My bibliography  Save this article

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

Author

Listed:
  • Dai, Jun
  • Zhou, Haigang
  • Zhao, Shaoquan

Abstract

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Suggested Citation

  • Dai, Jun & Zhou, Haigang & Zhao, Shaoquan, 2017. "Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 502-510.
    • Handle: RePEc:eee:phsmap:v:466:y:2017:i:c:p:502-510
    DOI: 10.1016/j.physa.2016.09.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116306811
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.09.056?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. Thomas Conlon & John Cotter, 2012. "An empirical analysis of dynamic multiscale hedging using wavelet decomposition," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(3), pages 272-299, March.
    2. Donald Lien & Keshab Shrestha, 2007. "An empirical analysis of the relationship between hedge ratio and hedging horizon using wavelet analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(2), pages 127-150, February.
    3. Mao, James C. T., 1970. "Models of Capital Budgeting, E-V VS E-S," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 4(5), pages 657-675, January.
    4. Wayne Y. Lee & Ramesh K. S. Rao, 1988. "Mean Lower Partial Moment Valuation and Lognormally Distributed Returns," Management Science, INFORMS, vol. 34(4), pages 446-453, April.
    5. Leon, Angel & Rubio, Gonzalo & Serna, Gregorio, 2005. "Autoregresive conditional volatility, skewness and kurtosis," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 599-618, September.
    6. Donald Lien & Yiu Kuen Tse, 1998. "Hedging time‐varying downside risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(6), pages 705-722, September.
    7. Francis In & Sangbae Kim, 2006. "The Hedge Ratio and the Empirical Relationship between the Stock and Futures Markets: A New Approach Using Wavelet Analysis," The Journal of Business, University of Chicago Press, vol. 79(2), pages 799-820, March.
    8. Demirer, Riza & Lien, Donald, 2003. "Downside risk for short and long hedgers," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 25-44.
    9. Donald Lien & Y. K. Tse, 2002. "Some Recent Developments in Futures Hedging," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 357-396, July.
    10. repec:bla:jecsur:v:16:y:2002:i:3:p:357-96 is not listed on IDEAS
    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. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    2. 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.

    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. 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.
    2. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    3. Jules Sadefo Kamdem & Zoulkiflou Moumouni, 2020. "Comparison of Some Static Hedging Models of Agricultural Commodities Price Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 631-655, September.
    4. 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).
    5. Jahangir Sultan & Antonios K. Alexandridis & Mohammad Hasan & Xuxi Guo, 2019. "Hedging performance of multiscale hedge ratios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1613-1632, December.
    6. Zoulkiflou Moumouni & Jules Sadefo-Kamdem, 2019. "New models of commodity risk hedging according to the behavior of economic decision-makers or Rollover Strategies," Working Papers hal-02417459, HAL.
    7. Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
    8. Mara Madaleno & Carlos Pinho, 2010. "Hedging Performance and Multiscale Relationships in the German Electricity Spot and Futures Markets," JRFM, MDPI, vol. 3(1), pages 1-37, December.
    9. 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.
    10. Shrestha, Keshab & Subramaniam, Ravichandran & Rassiah, Puspavathy, 2017. "Pure martingale and joint normality tests for energy futures contracts," Energy Economics, Elsevier, vol. 63(C), pages 174-184.
    11. Philippe Raimbourg & Paul Zimmermann, 2022. "Is normal backwardation normal? Valuing financial futures with a local index-rate covariance," Post-Print hal-04011013, HAL.
    12. Gurmeet Singh, 2017. "Estimating Optimal Hedge Ratio and Hedging Effectiveness in the NSE Index Futures," Jindal Journal of Business Research, , vol. 6(2), pages 108-131, December.
    13. Demirer, Riza & Lien, Donald & Shaffer, David R., 2005. "Comparisons of short and long hedge performance: the case of Taiwan," Journal of Multinational Financial Management, Elsevier, vol. 15(1), pages 51-66, February.
    14. Antonakakis, Nikolaos & Kizys, Renatas & Floros, Christos, 2014. "Dynamic Spillover Effects in Futures Markets," MPRA Paper 53876, University Library of Munich, Germany.
    15. Vedenov, Dmitry & Power, Gabriel J., 2022. "We don't need no fancy hedges! Or do we?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    16. Power, Gabriel J. & Eaves, James & Turvey, Calum & Vedenov, Dmitry, 2017. "Catching the curl: Wavelet thresholding improves forward curve modelling," Economic Modelling, Elsevier, vol. 64(C), pages 312-321.
    17. Kuang-Liang Chang, 2011. "The optimal value-at-risk hedging strategy under bivariate regime switching ARCH framework," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2627-2640.
    18. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    19. Hou, Yang & Holmes, Mark, 2017. "On the effects of static and autoregressive conditional higher order moments on dynamic optimal hedging," MPRA Paper 82000, University Library of Munich, Germany.
    20. Cotter, John & Hanly, Jim, 2015. "Performance of utility based hedges," Energy Economics, Elsevier, vol. 49(C), pages 718-726.

    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:eee:phsmap:v:466:y:2017:i:c:p:502-510. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.