Generalized parameter functions for option pricing
| Autor: | Andreou, Panayiotis C., Charalambous, Chris, Martzoukos, Spiros H. |
|---|---|
| Přispěvatelé: | Martzoukos, Spiros H. [0000-0002-4040-3096] |
| Rok vydání: | 2010 |
| Předmět: |
Economics and Econometrics
Semi-parametric approach Stochastic volatility Deterministic volatility functions Option pricing Nonparametric statistics Social Sciences Implied volatility Implied volatilities Economics and Business Valuation of options Econometrics Volatility smile Kurtosis Economics Volatility (finance) Finance Delta-hedging Parametric statistics |
| Zdroj: | Journal of Banking and Finance |
| ISSN: | 0378-4266 |
| DOI: | 10.1016/j.jbankfin.2009.08.027 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect