This paper analyzes the implications of autoregressive betas in single factor models for the statistical properties of stock returns. It is demonstrated that this assumption alone is sufficient to account for the most important stylized facts of stock returns, namely conditional...

The equivalence of the Beveridge-Nelson decomposition and the trend-cycle decomposition is well established. In this paper we argue that this equivalence is almost immediate when a Gaussian score-driven location model is considered. We also provide a natural extension towards heavy-tailed...

The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases,...

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken...

This paper proposes an extension to threshold-type switching models that lets the threshold variable be a linear combination of exogenous variables with unknown coefficients. An algorithm to estimate the model's parameters by least squares is provided and the validity of the methodological...