Estimation methods for stochastic volatility models: a survey
Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index. Copyright Blackwell Publishers Ltd, 2004.
Year of publication: |
2004
|
---|---|
Authors: | Broto, Carmen ; Ruiz, Esther |
Published in: |
Journal of Economic Surveys. - Wiley Blackwell. - Vol. 18.2004, 5, p. 613-649
|
Publisher: |
Wiley Blackwell |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Testing for Conditional Heteroscedasticity in the Components of Inflation
Broto, Carmen, (2009)
-
Testing for conditional heteroscedasticity in the components of inflation
Broto, Carmen, (2008)
-
Unobserved component models with asymmetric conditional variances
Broto, Carmen, (2006)
- More ...