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The hedging effectiveness of DAX futures

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Author Info
G. Lypny, M. Powalla
Abstract

Dynamic futures hedging strategies have been shown to be effective in a number of markets, but the gain in risk reduction over simple, constant hedges varies. This paper examines the hedging effectiveness of German stock index DAX futures and shows that the application of a dynamic hedging strategy based on a GARCH(1,1) covariance structure, combined with an error correction of the mean returns, yields economically significant in- and out-of-sample improvements in welfare over a simple constant hedge and over a dynamic hedge with the error correction but without the GARCH(1,1) covariance structure. A nonparametric test of the model's forecasts shows that it is able to predict both portfolio returns and investor utility significantly better than the simpler alternative models considered.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal The European Journal of Finance.

Volume (Year): 4 (1998)
Issue (Month): 4 (December)
Pages: 345-355
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Handle: RePEc:taf:eurjfi:v:4:y:1998:i:4:p:345-355

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Related research
Keywords: Hedging; Stock ; Index ; Futures; Garch ; Models; Dynamic ; Hedging;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Baillie, Richard T. & DeGennaro, Ramon P., 1990. "Stock Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(02), pages 203-214, June. [Downloadable!]
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  2. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September. [Downloadable!] (restricted)
  3. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March. [Downloadable!] (restricted)
  4. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May. [Downloadable!] (restricted)
  5. Cohen, Kalman J. & Hawawini, Gabriel A. & Maier, Steven F. & Schwartz, Robert A. & Whitcomb, David K., 1983. "Friction in the trading process and the estimation of systematic risk," Journal of Financial Economics, Elsevier, vol. 12(2), pages 263-278, August. [Downloadable!] (restricted)
  6. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August. [Downloadable!] (restricted)
  7. Fowler, David J. & Rorke, C. Harvey, 1983. "Risk measurement when shares are subject to infrequent trading : Comment," Journal of Financial Economics, Elsevier, vol. 12(2), pages 279-283, August. [Downloadable!] (restricted)
  8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Atreya Chakraborty, John T. Barkoulas, 1999. "Dynamic futures hedging in currency markets," European Journal of Finance, Taylor and Francis Journals, vol. 5(4), pages 299-314, December. [Downloadable!] (restricted)
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