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FRS17 and the Sterling Doubles A Corporate Yield Curve

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  • Frank Skinner

    ()
    (ICMA Centre, University of Reading)

  • Michalis Ioannides

    (Watson Wyatt LLP, UK)

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    Abstract

    The skewness in physical distributions of equity index returns and the implied volatility skew in the risk-neutral measure are subjects of extensive academic research. Much attention is now being focused on models that are able to capture time-varying conditional skewness and kurtosis. For this reason normal mixture GARCH(1,1) models have become very popular in financial econometrics. We introduce further asymmetries into this class of models by modifying the GARCH(1,1) variance processes to skewed variance processes with leverage effects. These asymmetric normal mixture GARCH models can differentiate between two different sources of asymmetry: a persistent asymmetry due to the different means in the conditional normal mixture distributions, and a dynamic asymmetry (the leverage effect) due to the skewed GARCH processes. Empirical results on five major equity indices first employ many statistical criteria to determine whether asymmetric (GJR and AGARCH) normal mixture GARCH models can improve on asymmetric normal and Student’s-t GARCH specifications. These models were also used to simulate implied volatility smiles for the S&P index, and we find that much the most realistic skews are obtained from a GARCH model with a mixture of two GJR variance components.

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    Bibliographic Info

    Paper provided by Henley Business School, Reading University in its series ICMA Centre Discussion Papers in Finance with number icma-dp2004-08.

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    Length: 24 pages
    Date of creation: Jun 2004
    Date of revision:
    Publication status: Published in International Journal of Theoretical & Applied Finance 2006, 9:2, 415-437
    Handle: RePEc:rdg:icmadp:icma-dp2004-08

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    Related research

    Keywords: Corporate Yield Curves; valuation of defined benefit liabilities;

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    References

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    1. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-67, May.
    2. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-89, October.
    3. Robert A. Jarrow, 2009. "The Term Structure of Interest Rates," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 69-96, November.
    4. Houweling, P. & Hoek, J. & Kleibergen, F.R., 1999. "The Joint Estimation of Term Structures and Credit Spreads," Econometric Institute Research Papers EI 9916-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-70, May.
    6. Mark Fisher & Douglas Nychka & David Zervos, 1995. "Fitting the term structure of interest rates with smoothing splines," Finance and Economics Discussion Series 95-1, Board of Governors of the Federal Reserve System (U.S.).
    7. McCulloch, J Huston, 1975. "The Tax-Adjusted Yield Curve," Journal of Finance, American Finance Association, vol. 30(3), pages 811-30, June.
    8. Daniel F. Waggoner, 1997. "Spline methods for extracting interest rate curves from coupon bond prices," Working Paper 97-10, Federal Reserve Bank of Atlanta.
    9. McCulloch, J Huston, 1971. "Measuring the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 44(1), pages 19-31, January.
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