Estimating stochastic volatility models through indirect inference
We propose as a tool for the estimation of stochastic volatility models two indirect inference estimators based on the choice of an autoregressive auxiliary model and an ARMA auxiliary model, respectively. These choices make the auxiliary parameter easy to estimate and at the same time allow the derivation of optimal indirect inference estimators. The results of some Monte Carlo experiments provide evidence that the indirect inference estimators perform well in finite sample, although less efficiently than Bayes and Simulated EM algorithms.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
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.
Volume (Year): 1 (1998)
Issue (Month): ConferenceIssue ()
|Contact details of provider:|| Postal: 2 Dean Trench Street, Westminster, SW1P 3HE|
Phone: +44 20 3137 6301
Web page: http://www.res.org.uk/
More information through EDIRC
|Order Information:||Web: http://www.ectj.org|