This article considers risk measures constructed under a discrete mixture-of-normal distribution on the innovations of a GARCH model with time-varying volatility. The authors use an approach based on a continuous empirical characteristic function to estimate the parameters of the model using...

In this paper, we explore the use of Independent Component Analysis (ICA) from the field of signal processing to model and estimate the dynamics of multivariate volatilities of financial asset returns in the GARCH framework. The resulting ICA-GARCH approach is shown to provide a computationally...

This paper provides a selected review of the recent developments and applications of mixture-of-normal (MN) distribution models in financial econometrics. One noted feature of the MN model is its flexibility in accommodating various shapes of continuous distributions, and its ability in...

This paper constructs Value at Risk (VaR) measures from a stochastic volatility model with a discrete bivariate mixture-of-normal error distribution - henceforth SV-MN. This volatility-gnerating model is able to accommodate many of the salient features of financial asset returns, such as...

In this paper, we propose the use of static and dynamic copulas to study the leverage effect in the S&P 500 index. Copula models can conveniently separate the leverage effect from the marginal distributions of the return and its volatility. Daily volatility is proxied by a measure of realized...

Increasing attention has been focused on the analysis of the realized volatility, which can be treated as a proxy for the true volatility. In this paper, we study the potential use of the realized volatility as a proxy in a stochastic volatility model estimation. We estimate the leveraged...

This paper develops a simple alternative estimation method for the GARCH models based on the empirical characteristic function. A set of Monte Carlo experiments is carried out to assess the performance of the proposed estimator. The results reveal that the proposed estimator has good finite...

This paper investigates alternative generalized method of moments (GMM) estimation procedures of a stochastic volatility model with realized volatility measures. The extended model can accommodate a more general correlation structure. General closed form moment conditions are derived to examine...

Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data...