This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information derived from domestic and US stock market news. By employing a double-threshold regression GARCH model to investigate four major index return series, we find significant...

This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information derived from domestic and US stock-market news. By employing a double-threshold regression GARCH model to investigate four major index-return series, we find significant...

Constructing multivariate conditional distributions for non-Gaussian return series has been a major research agenda recently. Copula GARCH models combine the use of GARCH models and a copula function to allow flexibility on the choice of marginal distributions and dependence structures. However,...

This paper studies a threshold extreme value distribution for modeling standardized financial returns. The main theme is tail asymmetry, which means that the left and right tails of the standardized return distribution are not identical. The peak-over-threshold idea in extreme value theory is...

In high dimensional data, relevant interactions can be difficult to identify due to the extremely large number of possible interactions among variables. Conventional methods use a screening stage to vastly reduce the dimension of the variable space before examining the interaction effect....

It is well known that volatility asymmetry exists in financial markets. This paper reviews and investigates recently developed techniques for Bayesian estimation and model selection applied to a large group of modern asymmetric heteroskedastic models. These include the GJR-GARCH, threshold...

A wide variety of conditional and stochastic variance models has been used to estimate latent volatility (or risk). In both the conditional and stochastic volatility literature, there has been some confusion between the definitions of asymmetry and leverage. In this paper, we first show the...

Most multivariate variance models suffer from a common problem, the “curse of dimensionalityâ€. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models...

Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even bias-corrected and consistent realized...

The paper proposes a general asymmetric multifactor Wishart stochastic volatility (AMWSV) diffusion process which accommodates leverage, feedback effects and multifactor for the covariance process. The paper gives the closed-form solution for the conditional and unconditional Laplace transform...