Statistical Inference for Random Variance Option Pricing
AbstractThis article deals with the estimation of continuous-time stochastic volatility models of option pricing. We argue that option prices are much more informative about the parameters than are asset prices. This is confirmed in a Monte Carlo experiment that compares two very simple strategies based on the different information sets. Both approaches are based on indirect inference and avoid any discretization bias by simulating the continuous-time model. We assume an Ornstein-Uhlenbeck process for the log of the volatility, a zero-volatility risk premium, and no leverage effect. We do not pursue asymptotic efficiency or specification issues; rather, we stick to a framework with no overidentifying restrictions and show that, given our option-pricing model, estimation based on option prices is much more precise in samples of typical size, without increasing the computational burden.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Toulouse - GREMAQ in its series Papers with number 95.403.
Length: 29 pages
Date of creation: 1995
Date of revision:
Contact details of provider:
Postal: GREMAQ, Universite de Toulouse I Place Anatole France 31042 - Toulouse CEDEX France.
Fax: 05 61 22 55 63
Web page: http://www-gremaq.univ-tlse1.fr/
More information through EDIRC
ECONOMETRICS; STATISTICS; PRICES;
Other versions of this item:
- Pastorello, Sergio & Renault, Eric & Touzi, Nizar, 2000. "Statistical Inference for Random-Variance Option Pricing," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 358-67, July.
- S, Pastorello & E, Renault & N, Touzi, 1997. "Statistical Inference for Random Variance Option Pricing," Working Papers 97-60, Centre de Recherche en Economie et Statistique.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Li, Tong, 2010. "Indirect inference in structural econometric models," Journal of Econometrics, Elsevier, vol. 157(1), pages 120-128, July.
- Cheng, Ai-ru (Meg) & Gallant, A. Ronald & Ji, Chuanshu & Lee, Beom S., 2008. "A Gaussian approximation scheme for computation of option prices in stochastic volatility models," Journal of Econometrics, Elsevier, vol. 146(1), pages 44-58, September.
- Max O. Souza & Jorge P. Zubelli, 2007. "On The Asymptotics Of Fast Mean-Reversion Stochastic Volatility Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 817-835.
- Sergio Pastorello & Valentin Patilea & Éric Renault, 2003.
"Iterative and Recursive Estimation in Structural Non-Adaptive Models,"
CIRANO Working Papers
- Pastorello, Sergio & Patilea, Valentin & Renault, Eric, 2003. "Iterative and Recursive Estimation in Structural Nonadaptive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 449-82, October.
- Torben G. Andersen & Luca Benzoni & Jesper Lund, 2001.
"An Empirical Investigation of Continuous-Time Equity Return Models,"
NBER Working Papers
8510, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous-Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, 06.
- Fornari, F. & Mele, A., 1998.
"ARCH Models and Option Pricing: The Continuous Time Connection,"
9830, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..
- Antonio Mele & Fabio Fornari, 1999. "ARCH Models and Option Pricing: the Continuous-Time Connection," Computing in Economics and Finance 1999 113, Society for Computational Economics.
- F. Fornari & A. Mele, 1998. "ARCH Models and Option Pricing : The Continuous Time Connection," THEMA Working Papers 98-30, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Garcia, René & Lewis, Marc-André & Pastorello, Sergio & Renault, Éric, 2011. "Estimation of objective and risk-neutral distributions based on moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 22-32, January.
- Antonio Mele & Filippo Altissimo, 2004.
"Simulated Nonparametric Estimation of Continuous Time Models of Asset Prices and Returns,"
FMG Discussion Papers
dp476, Financial Markets Group.
- Filippo Altissimo & Antonio Mele, 2004. "Simulated nonparametric estimation of continuous time models of asset prices and returns," LSE Research Online Documents on Economics 24674, London School of Economics and Political Science, LSE Library.
- F. Comte & L. Coutin & E. Renault, 2012. "Affine fractional stochastic volatility models," Annals of Finance, Springer, vol. 8(2), pages 337-378, May.
- A. S. Hurn & K. A. Lindsay & V. L. Martin, 2003. "On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 45-63, 01.
- Griffin, J.E. & Steel, M.F.J., 2006.
"Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility,"
Journal of Econometrics,
Elsevier, vol. 134(2), pages 605-644, October.
- James E. Griffin & Mark F.J. Steel, 2002. "Inference With Non-Gaussian Ornstein-Uhlenbeck Processes for Stochastic Volatility," Econometrics 0201002, EconWPA, revised 04 Apr 2003.
- Raknerud, Arvid & Skare, Øivind, 2012. "Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3260-3275.
- Jeremy Graveline & Irina Zviadadze & Mikhail Chernov, 2012. "Crash Risk in Currency Returns," 2012 Meeting Papers 753, Society for Economic Dynamics.
- René Garcia & Eric Ghysels & Éric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel).
If references are entirely missing, you can add them using this form.