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Hedging performance of Chinese stock index futures: An empirical analysis using wavelet analysis and flexible bivariate GARCH approaches

  • Hou, Yang
  • Li, Steven
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    In this paper, we assess the hedging performance of the newly established CSI 300 stock index futures over some short hedging horizons. We use wavelet analysis as well as conventional models (naïve, ordinary least squares, and error-correction) to compute the constant hedge ratios. The constant conditional correlation (CCC) and dynamic conditional correlation (DCC) bivariate generalised autoregressive conditional heteroskedasticity (BGARCH) specifications are employed to calculate the time-varying hedge ratios. Overall, we find that the CSI 300 stock index futures can be an effective hedging tool. Among the constant hedge ratio models, the wavelet analysis yields the best in-sample hedging performance, though its out-of-sample hedging performance is similar to other models. Comparing the time-varying ratio models, the CCC BGARCH model is better in terms of in-sample hedging effectiveness while for out-of-sample hedging performance, the DCC model is better with short hedging horizons and CCC model is more favourable with long hedging horizons. Finally, the question whether time-varying ratios outperform constant ratios depends on the length of the hedging horizon. Short horizons favour BGARCH hedging models while long horizons favour constant hedging ratio models.

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    Article provided by Elsevier in its journal Pacific-Basin Finance Journal.

    Volume (Year): 24 (2013)
    Issue (Month): C ()
    Pages: 109-131

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    Handle: RePEc:eee:pacfin:v:24:y:2013:i:c:p:109-131
    Contact details of provider: Web page: http://www.elsevier.com/locate/pacfin

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    1. 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 109-24, April-Jun.
    2. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-70, March.
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    5. Bera, Anil K. & Kim, Sangwhan, 2002. "Testing constancy of correlation and other specifications of the BGARCH model with an application to international equity returns," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 171-195, March.
    6. 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.
    7. Susmel, Raul & Engle, Robert F., 1994. "Hourly volatility spillovers between international equity markets," Journal of International Money and Finance, Elsevier, vol. 13(1), pages 3-25, February.
    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. Lien, Donald & Tse, Y K, 2002. " Some Recent Developments in Futures Hedging," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 357-96, July.
    10. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2011. "A copula–multifractal volatility hedging model for CSI 300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4260-4272.
    11. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    12. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-50, July.
    13. Chris Brooks & Olan T. Henry & Gita Persand, 2002. "The Effect of Asymmetries on Optimal Hedge Ratios," The Journal of Business, University of Chicago Press, vol. 75(2), pages 333-352, April.
    14. Engle, Robert F & Gonzalez-Rivera, Gloria, 1991. "Semiparametric ARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 345-59, October.
    15. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
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