We analyze daily changes of two log foreign exchange (FX) rates involving the Deutsche Mark (DEM) for the period 1975 - 1998, namely FX-rates measured against the US dollar (USD) and the Japanese yen (JPY). Ta account for volatility e1ustering we fit a GARCH(l,l)-model with leptokurtic...

Multivariate Volatility Models belong to the class of nonlinear models for financial data. Here we want to focus on multivariate GARCH models. These models assume that the variance of the innovation distribution follows a time dependent process conditional on information which is generated by...

This article is concerned with the dynamic behaviour of UK unemployment. However, instead of using traditional approaches based on I(0) stationary or I(1) (integrated and/or cointegrated) models, we use the fractional integration framework. In doing so, we allow for a more careful study of the...

Let a process SI , ... ,ST obey the conditionally heteroskedastic equation St = Vt Et whcrc Et is a random noise and Vt is the volatility coefficient which in turn obeys an autoregression type equation log v t = w + a S t- l + nt with an additional noise nt. We consider the situation which the...

This paper uses fractional integration and cointegration in order to model the DM/dollar and the yen/dollar real exchange rates in terms of both monetary and real factors, more specifically real interest rate and labour productivity differentials. We find that whilst the individual series may be...

In this article we model the log of the U.S. and the U.K. real oil prices in terms of fractionally integrated processes with a mean shift. We use different versions of the tests of Robinson (1994), which have standard null and local limit distributions. The results indicate that if we model the...

Fractionally integrated models with the disturbances following a Bloomfield (1973) exponential spectral model are proposed in this article for modelling the U.K. unemployment. This enables us a better understanding of the low-frequency dynamics affecting the series, without relying on any...

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods. --...