IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpfi/0512018.html
   My bibliography  Save this paper

Hedge ratio estimation and hedging effectiveness: the case of the S&P 500 stock index futures contract

Author

Listed:
  • Dimitris Kenourgios

    (University of Athens)

  • Aristeidis Samitas

    (University of Aegean)

  • Panagiotis Drosos

    (University of Sheffield)

Abstract

This paper investigates the hedging effectiveness of the Standard & Poor’s (S&P) 500 stock index futures contract using weekly settlement prices for the period July 3rd, 1992 to June 30th, 2002. Particularly, it focuses on three areas of interest: the determination of the appropriate model for estimating a hedge ratio that minimizes the variance of returns; the hedging effectiveness and the stability of optimal hedge ratios through time; an in-sample forecasting analysis in order to examine the hedging performance of different econometric methods. The hedging performance of this contract is examined considering alternative methods, both constant and time-varying, for computing more effective hedge ratios. The results suggest the optimal hedge ratio that incorporates nonstationarity, long run equilibrium relationship and short run dynamics is reliable and useful for hedgers. Comparisons of the hedging effectiveness and in-sample hedging performance of each model imply that the error correction model (ECM) is superior to the other models employed in terms of risk reduction. Finally, the results for testing the stability of the optimal hedge ratio obtained from the ECM suggest that it remains stable over time.

Suggested Citation

  • Dimitris Kenourgios & Aristeidis Samitas & Panagiotis Drosos, 2005. "Hedge ratio estimation and hedging effectiveness: the case of the S&P 500 stock index futures contract," Finance 0512018, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0512018
    Note: Type of Document - pdf; pages: 23
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/fin/papers/0512/0512018.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    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. Zanotti, Giovanna & Gabbi, Giampaolo & Geranio, Manuela, 2010. "Hedging with futures: Efficacy of GARCH correlation models to European electricity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(2), pages 135-148, April.
    2. John Hua Fan & Eduardo Roca & Alexandr Akimov, 2010. "Hedging With Futures Contract: Estimation and Performance Evaluation of Optimal Hedge Ratios in the European Union Emissions Trading Scheme," Discussion Papers in Finance finance:201009, Griffith University, Department of Accounting, Finance and Economics.
    3. Elisa Scarpa & Matteo Manera, 2008. "Pricing and hedging illiquid energy derivatives: An application to the JCC index," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(5), pages 464-487, 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. Seiler, Volker, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 160-179.
    2. Beran, Jan & Feng, Yuanhua, 1999. "Local Polynomial Estimation with a FARIMA-GARCH Error Process," CoFE Discussion Papers 99/08, University of Konstanz, Center of Finance and Econometrics (CoFE).
    3. Corbet, Shaen & Larkin, Charles & McMullan, Caroline, 2020. "The impact of industrial incidents on stock market volatility," Research in International Business and Finance, Elsevier, vol. 52(C).
    4. Cho, Guedae & Kim, MinKyoung & Koo, Won W., 2003. "Relative Agricultural Price Changes In Different Time Horizons," 2003 Annual meeting, July 27-30, Montreal, Canada 22249, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    6. Umar, Muhammad & Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Furqan, Mehreen, 2023. "Asymmetric volatility structure of equity returns: Evidence from an emerging market," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 330-336.
    7. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    8. Lahmiri, Salim & Bekiros, Stelios, 2017. "Disturbances and complexity in volatility time series," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 38-42.
    9. Hao Chen & Qiulan Wan & Yurong Wang, 2014. "Refined Diebold-Mariano Test Methods for the Evaluation of Wind Power Forecasting Models," Energies, MDPI, vol. 7(7), pages 1-14, July.
    10. Tomanova, Lucie, 2013. "Exchange Rate Volatility and the Foreign Trade in CEEC," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 267, Ekonomik Yaklasim Association.
    11. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    12. Jumah, Adusei & Kunst, Robert M., 2001. "The Effects of Exchange-Rate Exposures on Equity Asset Markets," Economics Series 94, Institute for Advanced Studies.
    13. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    14. Gruener Hans Peter & Hayo Bernd & Hefeker Carsten, 2009. "Unions, Wage Setting and Monetary Policy Uncertainty," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-25, October.
    15. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    16. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    17. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2024. "Testing Granger non-causality in expectiles," Econometric Reviews, Taylor & Francis Journals, vol. 43(1), pages 30-51, January.
    18. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    19. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    20. Chang, Chia-Lin & Hsu, Hui-Kuang, 2013. "Modelling Volatility Size Effects for Firm Performance: The Impact of Chinese Tourists to Taiwan," MPRA Paper 45691, University Library of Munich, Germany.

    More about this item

    Keywords

    Hedging effectiveness; minimum variance hedge ratio (MVHR); hedging models; Standard & Poor’s 500 stock index futures;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:wpa:wuwpfi:0512018. 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: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.