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Pricing Of S&P 100 Index Options Based On Garch Volatility Estimates

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  • Ayla Ogus

    (Izmir University of Economics)

Abstract

This paper is a contribution to the vast literature on the inefficiency in the index options markets. Previous research has found that trading based on implied volatility forecasts do not generate positive profits for the S&P 500 index options but GARCH volatility forecasts do. Trading based on implied volatility forecasts for the S&P 100 index options also fail to generate profits in excess of transaction costs. This paper shows that trading based on GARCH volatility forecast generates profits in excess of transaction costs for the S&P 100 index options hence there is systematic mispricing in the S&P index options markets. GARCH models fair well due to their flexibility to incorporate asymmetric and nonlinear volatility effects. Improved pricing models should work as well or better.

Suggested Citation

  • Ayla Ogus, 2005. "Pricing Of S&P 100 Index Options Based On Garch Volatility Estimates," Finance 0504005, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0504005
    Note: Type of Document - pdf; pages: 30
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    References listed on IDEAS

    as
    1. Ackert, Lucy F. & Tian, Yisong S., 2001. "Efficiency in index options markets and trading in stock baskets," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1607-1634, September.
    2. Bent Jesper Christensen & Charlotte Strunk Hansen, 2002. "New evidence on the implied-realized volatility relation," The European Journal of Finance, Taylor & Francis Journals, vol. 8(2), pages 187-205, June.
    3. Evnine, Jeremy & Rudd, Andrew, 1985. "Index Options: The Early Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 743-756, July.
    4. Galai, Dan, 1977. "Tests of Market Efficiency of the Chicago Board Options Exchange," The Journal of Business, University of Chicago Press, vol. 50(2), pages 167-197, April.
    5. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-294, October-D.
    6. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    7. Stephen Figlewski, 1997. "Forecasting Volatility," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 6(1), pages 1-88, February.
    8. Robert F. Engle & Alex Kane & Jaesun Noh, 1993. "Index-Option Pricing with Stochastic Volatility and the Value of Accurate Variance Forecasts," NBER Working Papers 4519, National Bureau of Economic Research, Inc.
    9. Kamara, Avraham & Miller, Thomas W., 1995. "Daily and Intradaily Tests of European Put-Call Parity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(4), pages 519-539, December.
    10. Harvey, Campbell R & Whaley, Robert E, 1991. "S&P 100 Index Option Volatility," Journal of Finance, American Finance Association, vol. 46(4), pages 1251-1261, September.
    11. Latane, Henry A & Rendleman, Richard J, Jr, 1976. "Standard Deviations of Stock Price Ratios Implied in Option Prices," Journal of Finance, American Finance Association, vol. 31(2), pages 369-381, May.
    12. Duan, Jin-Chuan & Zhang, Hua, 2001. "Pricing Hang Seng Index options around the Asian financial crisis - A GARCH approach," Journal of Banking & Finance, Elsevier, vol. 25(11), pages 1989-2014, November.
    13. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    14. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    15. Day, Theodore E. & Lewis, Craig M., 1988. "The behavior of the volatility implicit in the prices of stock index options," Journal of Financial Economics, Elsevier, vol. 22(1), pages 103-122, October.
    16. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
    17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    GARCH; S&P100; index options;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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