Although volatility clustering has a long history as a salient empirical regularity
characterizing high-frequency speculative prices, it was not until recently that applied …

The aim of this survey paper is to provide an account of some of the important developments
in the autoregressive conditional heteroskedasticity (ARCH) model since its inception in a …

Provides a comprehensive and updated study of GARCH models and their applications in
finance, covering new developments in the discipline This book provides a comprehensive …

This paper defines the news impact curve which measures how new information is
incorporated into volatility estimates. Various new and existing ARCH models including a …

1.1 Introduction Research into time series models of changing variance and covariance,
which I will collectively call volatility models, has exploded in the last ten years. This activity …

ARCH models often impute a lot of persistence to stock volatility and yet give relatively poor
forecasts. One explanation is that extremely large shocks, such as the October 1987 crash …

Engle's ARCH model is extended to permit parametric specifications for conditional
dependence beyond the mean and variance. The suggestion is to model the conditional …

We study the correlation of monthly excess returns for seven major countries over the period
1960-90. We find that the international covariance and correlation matrices are unstable …

Modeling the dependency between stock market returns is a difficult task when returns
follow a complicated dynamics. When returns are non-normal, it is often simply impossible to …

The paper provides a survey of the work that has been done in financial econometrics in the
past decade. It proceeds by first establishing a set of stylized facts that are characteristics of …