Parametric pricing of higher order moments in S&P500 options
Article first published online: 8 DEC 2004
Copyright © 2004 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
Volume 20, Issue 3, pages 377–404, March/April 2005
How to Cite
Lim, G. C., Martin, G. M. and Martin, V. L. (2005), Parametric pricing of higher order moments in S&P500 options. J. Appl. Econ., 20: 377–404. doi: 10.1002/jae.762
- Issue published online: 14 APR 2005
- Article first published online: 8 DEC 2004
- Manuscript Revised: 30 SEP 2003
- Manuscript Received: 1 MAR 2002
- Australian Research Council.
A general parametric framework based on the generalized Student t-distribution is developed for pricing S&P500 options. Higher order moments in stock returns as well as time-varying volatility are priced. An important computational advantage of the proposed framework over Monte Carlo-based pricing methods is that options can be priced using one-dimensional quadrature integration. The empirical application is based on S&P500 options traded on select days in April 1995, a total sample of over 100,000 observations. A range of performance criteria are used to evaluate the proposed model, as well as a number of alternative models. The empirical results show that pricing higher order moments and time-varying volatility yields improvements in the pricing of options, as well as correcting the volatility skew associated with the Black–Scholes model. Copyright © 2004 John Wiley & Sons, Ltd.