## Abstract The authors explore the finite sample properties of the generalized autoregressive conditional heteroscedasticity (GARCH) option pricing model proposed by S. L. Heston and S. Nandi (2000). Simulation results show that the maximum likelihood estimators of the GARCH process may contain su
An empirical investigation of the GARCH option pricing model: Hedging performance
✍ Scribed by Haynes H. M. Yung; Hua Zhang
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 160 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0270-7314
No coin nor oath required. For personal study only.
✦ Synopsis
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
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