Threshold-asymmetric volatility models for integer-valued time series

Stochastic volatility models for ordinal valued time series with application to finance

In this paper we introduce a new class of models, called OSV, by combining an ordinal response model and the idea of stochastic volatility. Corresponding time series occur in high-frequency finance when the stocks are traded on a coarse grid. For parameter estimation we develop an efficient Grouped Move Multigrid Monte Carlo (GM-MGMC) sampler. This sampler is based on a scale transformation gro...

Threshold Models for Trended Time Series

This paper presents the theoretical development of new threshold autoregressive models based on trended time series. The theoretical arguments underlying the models are outlined and a nonlinear economic model is used to derive the speci cation of the empirical econometric models. Estimation and testing issues are considered and analysed. Additionally we apply the models to the empirical investi...

The Combined Poisson Inma(2) Models for Integer-valued Time Series

In this paper, we introduce a new combined integer-valued moving average model of order 2 with poisson innovation, denoted by PCINMA(2). We consider some properties of this process, such as expectation, variance, autocovariance function. Stationary and ergodicity are obtained. We estimate the unknown parameters by using Yule-Walker estimation, and use simulation to assess the performance of Yul...

Time Series Analysis: Conditional Volatility Models

Specification Testing for Multivariate Time Series Volatility Models

Volatility models have been playing an important role in economics and finance. Using a multivariate generalized spectral approach, we propose a new class of generally applicable omnibus tests for univariate and multivariate volatility models. Both GARCH models and stochastic volatility models are covered. Our tests have a convenient asymptotic null N(0,1) distribution, and can detect a wide ra...