Generalized parameter functions for option pricing |
| |
Authors: | Panayiotis C Andreou Chris Charalambous Spiros H Martzoukos |
| |
Institution: | 1. Durham Business School, Durham University, Mill Hill Lane, DH1 3LB Durham, UK;2. Dept. of Public and Business Administration, University of Cyprus, P.O. Box 20537, 1678 Nicosia, Cyprus |
| |
Abstract: | We extend the benchmark nonlinear deterministic volatility regression functions of Dumas et al. (1998) to provide a semi-parametric method where an enhancement of the implied parameter values is used in the parametric option pricing models. Besides volatility, skewness and kurtosis of the asset return distribution can also be enhanced. Empirical results, using closing prices of the S&P 500 index call options (in one day ahead out-of-sample pricing tests), strongly support our method that compares favorably with a model that admits stochastic volatility and random jumps. Moreover, it is found to be superior in various robustness tests. Our semi-parametric approach is an effective remedy to the curse of dimensionality presented in nonparametric estimation and its main advantage is that it delivers theoretically consistent option prices and hedging parameters. The economic significance of the approach is tested in terms of hedging, where the evaluation and estimation loss functions are aligned. |
| |
Keywords: | G13 G14 |
本文献已被 ScienceDirect 等数据库收录! |
|