An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily asset price range is provided. The range is defined as the difference between the highest and lowest log intra-day asset price. A general model specification is proposed, allowing...

There is substantial evidence that many financial time series exhibit leptokurtosis and volatility clustering. We compare the two most commonly used statistical distributions in empirical analysis to capture these features: the t distribution and the generalized error distribution (GED). A...

The major goal of this paper is to examine the hypothesis that stock returns and return volatility are asymmetric, threshold nonlinear, functions of change in trading volume. A minor goal is to examine whether return spillover effects also display such asymmetry. Employing a double-threshold...

In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both...

We make use of the voluntary HIV and syphilis test results conducted at five gay saunas in Taipei from August of 1999 to end of 2002 to estimate the number of HIV-positive gay saunas patrons in Taipei area by utilizing Hierarchical Bayes method in Generalized Removal Model for Open Populations...

We propose a nonlinear smooth transition conditional autoregressive range (CARR) model for capturing smooth volatility asymmetries in international financial stock markets, building on recent work on smooth transition conditional duration modelling. An adaptive Markov chain Monte Carlo scheme is...

Some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models are proposed that incorporate intra-day price ranges. Model estimation is performed using a Bayesian approach via the link with the Skewed–Laplace distribution. The performances of a range of risk models during the...

Heterogeneity in many datasets stems from the different behaviors of several underlying groups or subpopulations. The aim of this paper is to classify observations in such a dataset into these latent groups when each group's behavior is piecewise linearly related to a set of covariates. We...

Smoothly time-varying (TV) GARCH models via an asymmetric logistic function mechanism are proposed, which are incorporated into the conditional volatility equation for capturing smooth structural breaks in the volatility of financial time series. The proposed models allow smooth transitions of...