We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

This paper investigates, in a particular parametric framework, the geometric meaning of joint unpredictability for a bivariate discrete process. In particular, the paper provides a characterization of the joint unpredictability in terms of distance between information sets in an Hilbert space.

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...

We develop a Bayesian test for structural change at an unknown changepoint in Markov-switching models. Unlike the usual Bayesian treatment of the unknown changepoint problem in the literature, we cast the problem into a `model selection' framework. This is done by adopting a prior for the shift...

This research involved developing an optimal stock investment decision strategy which offers minimum risk to the potential investor for counters listed on the Zimbabwe Stock Exchange. Three counters were compared namely Econet Wireless, Delta and Old Mutual. The first phase of the project...

The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single-equation Markov-switching (MS) models for two cases: when leading information is available and when it is not. The results show that single-equation MS models tend to perform...

This paper reviews recent developments in nonparametric identi.cation of mea- surement error models and their applications in applied microeconomics, in particular, in empirical industrial organization and labor economics. Measurement error models describe mappings from a latent distribution to...

In this paper we investigate the forecast performance of nonlinear error-correction models with regime switching. In particular, we focus on threshold and Markov-switching error-correction models where adjustment towards long-run equilibrium is nonlinear and discontinuous. Our simulation study...

In this paper we solve the discrete time mean-variance hedging problem when asset returns follow a multivariate autoregressive hidden Markov model. Time dependent volatility and serial dependence are well established properties of financial time series and our model covers both. To illustrate...