Threshold Arch Models and Asymmetries in Volatility SUMMARY This paper attempts to enlarge the class of Threshold Heteroscedastic ~ o d e l (sT ARCH) introduced by Zakoi'an (1991a). We show that it is possible to relax the positivity const...

Testing for Arch in the Presence of Additive Outliers SUMMARY In this paper we investigate the properties of the Lagrange Multiplier [LM] test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the pre...

Strong Consistency of Estimators for Multivariate Arch Models This paper deals with the asymptotic properties of quasi-maximum likelihood estimators for multivariate heteroskedastic models. For a general model, we give conditions under whi...

Multivariate Simultaneous Generalized Arch This paper presents theoretical results on the formulation and estimation of multivariate generalized ARCH models within simultaneous equations systems. A new parameterization of the multivariate...

Asymptotically Optimal Smoothing with Arch Models Suppose an observed time series is generated by a stochastic volatility model-i.e., there is an unobservable state variable controlling the volatility of the innovations in the series. As s...

Asymptotic Theory for ARCH Models_ Estimation and Testing ANDREWA. WEISS University of Southern California at Los Angeles In the context of a linear dynamic model with moving average errors, we consider a heteroscedastic model which repres...

Asymptotic Filtering Theory for Univariate Arch Models 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? Thi...

An Empirical Analysis of Alternative Parametric ARCH Models GEOFFREY F. LOUDON, WING H. WATT^ AND PRADEEP K. YADAVc* Macquarie University, Australia b~~~ Bank, Singapore 'Department of Accounting and Finance, University of Strathclyde, 100...

Adaptive Estimation in Arch Models OLIVERLINTON Nuffield College We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH(P)process. We do not assume a funct...

The GLS Transformation Matrix and a Semi-Recursive Estimator for the Linear Regression Model with Arma Errors JOHNW. GALBRAITHAND VICTORIA ZINDE-WALSH McGill University For a general stationary ARMA(p,q)process u we derive the exact form o...