The finite sample properties of the state space methods applied to long memory time series are analyzed through Monte Carlo simulations. The state space setup allows to introduce a novel modeling approach in the long memory framework, which directly tackles measurement errors and random level...

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with time varying parameters. The parameters are estimated by means of a sequential matching procedure which adopts as an auxiliary model a time-varying generalization of the HAR...

A major problem in applying neural networks is specifying the sizeof the network. Even for moderately sized networks the number ofparameters may become large compared to the number of data. In thispaper network performance is examined while reducing the size of thenetwork through the use of...

We construct models which enable a decision maker to analyse the implications of typical time series patterns of daily exchange rates for currency risk management. Our approach is Bayesian where extensive use is made of Markov chain Monte Carlo methods. The effects of several model...

Internationally operating firrns naturally face the decision whether or not to hedge the currency risk implied by foreign investments. In a recent paper, Bos, Mahieu and van Dijk (2000) evaluate the returns from optimal and alternative currency hedging strategies, for a series of 7 models, using...