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An empirical investigation of the GARCH option pricing model: Hedging performance

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  • Haynes H. M. Yung
  • Hua Zhang

Abstract

In this article, we study the empirical performance of the GARCH option pricing model relative to the ad hoc Black‐Scholes (BS) model of Dumas, Fleming, and Whaley. Specifically, we investigate the empirical performance of the option pricing model based on the exponential GARCH (EGARCH) process of Nelson. Using S&P 500 options data, we find that the EGARCH model performs better than the ad hoc BS model both in terms of in‐sample valuation and out‐of‐sample forecasting. However, the superiority of out‐of‐sample performance EGARCH model over the ad hoc BS model is small and insignificant except in the case of deep‐out‐of‐money put options. The out‐performance diminishes as one lengthens the forecasting horizon. Interestingly, we find that the more complicated EGARCH model performs worse than the ad hoc BS model in hedging, irrespective of moneyness categories and hedging horizons. For at‐the‐money and out‐of‐the‐money put options, the underperformance of the EGARCH model in hedging is statistically significant. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:1191–1207, 2003

Suggested Citation

  • Haynes H. M. Yung & Hua Zhang, 2003. "An empirical investigation of the GARCH option pricing model: Hedging performance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(12), pages 1191-1207, December.
    • Handle: RePEc:wly:jfutmk:v:23:y:2003:i:12:p:1191-1207
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    Cited by:

    1. Pascal François & Lars Stentoft, 2021. "Smile‐implied hedging with volatility risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1220-1240, August.
    2. Liu, Yanxin & Li, Johnny Siu-Hang & Ng, Andrew Cheuk-Yin, 2015. "Option pricing under GARCH models with Hansen's skewed-t distributed innovations," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 108-125.
    3. Han, Chuan-Hsiang & Lai, Yongzeng, 2010. "A smooth estimator for MC/QMC methods in finance," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 536-550.
    4. Yang, Chih-Yuan & Jhang, Ling-Jhen & Chang, Chia-Chien, 2016. "Do investor sentiment, weather and catastrophe effects improve hedging performance? Evidence from the Taiwan options market," Pacific-Basin Finance Journal, Elsevier, vol. 37(C), pages 35-51.
    5. Han, Chuan-Hsiang & Chang, Chien-Hung & Kuo, Chii-Shyan & Yu, Shih-Ti, 2015. "Robust hedging performance and volatility risk in option markets: Application to Standard and Poor's 500 and Taiwan index options," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 160-173.
    6. Aparna Bhat & Kirti Arekar, 2016. "Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(3), pages 123-136, March.

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