Logo Logo

GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study, Journal of Business & Economic Statistics

Abstract

We examine alternative generalized method of moments procedures for estimation of a stochastic autoregressive volatility model by Monte Carlo methods. We document the existence of a trade-off between the number of moments, or information, included in estimation and the quality, or precision, of the objective function used for estimation. Furthermore, an approximation to the optimal weighting matrix is used to explore the impact of the weighting matrix for estimation, specification testing, and inference procedures. The results provide guidelines that help achieve desirable small-sample properties in settings characterized by strong conditional heteroscedasticity and correlation among the moments.

Type

Article

Author(s)

Torben Andersen, Tim Bollerslev

Date Published

1996

Citations

Andersen, Torben, and Tim Bollerslev. 1996. GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study. Journal of Business & Economic Statistics. 14(3): 328-352.

KELLOGG INSIGHT

Explore leading research and ideas

Find articles, podcast episodes, and videos that spark ideas in lifelong learners, and inspire those looking to advance in their careers.
learn more

COURSE CATALOG

Review Courses & Schedules

Access information about specific courses and their schedules by viewing the interactive course scheduler tool.
LEARN MORE

DEGREE PROGRAMS

Discover the path to your goals

Whether you choose our Full-Time, Part-Time or Executive MBA program, you’ll enjoy the same unparalleled education, exceptional faculty and distinctive culture.
learn more