Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

5 Issues per year


IMPACT FACTOR 2016: 0.649

CiteScore 2016: 0.63

SCImago Journal Rank (SJR) 2016: 0.546
Source Normalized Impact per Paper (SNIP) 2016: 0.793

Mathematical Citation Quotient (MCQ) 2016: 0.03

Online
ISSN
1558-3708
See all formats and pricing
More options …
Volume 8, Issue 2

Issues

Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers

Kai Ming Lee / Siem Jan Koopman
Published Online: 2004-05-18 | DOI: https://doi.org/10.2202/1558-3708.1210

In this paper, we describe and compare two simulated Maximum Likelihood estimation methods for a basic stochastic volatility model. For both methods, the likelihood function is estimated using importance sampling techniques. Based on a Monte Carlo study, we assess which method is more effective. Further, we validate the two methods using diagnostic importance sampling test procedures. Stochastic volatility models with Gaussian and Student-t distributed disturbances are considered.

This article offers supplementary material which is provided at the end of the article.

About the article

Published Online: 2004-05-18


Citation Information: Studies in Nonlinear Dynamics & Econometrics, Volume 8, Issue 2, ISSN (Online) 1558-3708, DOI: https://doi.org/10.2202/1558-3708.1210.

Export Citation

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

Supplementary Article Materials

Comments (0)

Please log in or register to comment.
Log in