• DocumentCode
    3413816
  • Title

    Pricing S&P 500 index options with Heston´s model

  • Author

    Zhang, Jin E. ; Shu, Jinghong

  • Author_Institution
    Dept. of Finance, Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • fYear
    2003
  • fDate
    20-23 March 2003
  • Firstpage
    85
  • Lastpage
    92
  • Abstract
    This paper studies the price of S&P 500 index options by using Heston´s (1993) stochastic volatility option pricing model. The Heston model is calibrated by a two-step estimation procedure to incorporate both the information from time-series asset return and the information from cross-sectional option data. We find that both the Black-Scholes model and the Heston model overprice the out-of-the-money option and under price the in-the-money options, but the degree of the bias is different. The Heston model significantly outperforms the Black-Scholes model in almost all moneyness-maturity group. On average, the Heston model can reduce pricing errors by about 25%. However, pricing bias still exists in the Heston model, In particular, the Heston model always overprices short-term options, indicating that some other factors, such as the random jump, may also be needed to explain the option price.
  • Keywords
    costing; economic cybernetics; parameter estimation; statistical analysis; stock markets; time series; Black-Scholes model; Heston model; cross-sectional option data; index options; pricing errors; random jump; stochastic volatility option pricing model; time-series asset return; two-step estimation procedure; Calibration; Computational modeling; Diffusion processes; Econometrics; Finance; International trade; Parameter estimation; Pricing; Stochastic processes; Structural engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Financial Engineering, 2003. Proceedings. 2003 IEEE International Conference on
  • Print_ISBN
    0-7803-7654-4
  • Type

    conf

  • DOI
    10.1109/CIFER.2003.1196246
  • Filename
    1196246