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- Title
ASYMPTOTIC FILTERING THEORY FOR UNIVARIATE ARCH MODELS.
- Authors
Nelson, Daniel B.; Foster, Dean P.
- Abstract
Many researchers have employed ARCH models to estimate conditional variances and covariances. How successfully can ARCH models carry out this estimation when they are misspecified? This paper employs continuous record asymptotics to approximate the distribution of the measurement error. This allows us to (a) compare the efficiency of various ARCH models, (b) characterize the impact of different kinds of misspecification (e.g., "fat-tailed" errors, misspecified conditional means) on efficiency, and (c) characterize asymptotically optimal ARCH conditional variance estimates. We apply our results to derive optimal ARCH filters for three diffusion models, and to examine in detail the filtering properties of GARCH(1,1), AR(1) EGARCH, and the model of Taylor (1986) and Schwert (1989).
- Subjects
ASYMPTOTIC theory in econometrics; ANALYSIS of variance; MATHEMATICAL models; STOCHASTIC analysis; ECONOMICS; STATISTICS
- Publication
Econometrica, 1994, Vol 62, Issue 1, p1
- ISSN
0012-9682
- Publication type
Article
- DOI
10.2307/2951474