This paper considers factor forecasting with national versus factor forecasting withinternational data. We forecast German GDP based on a large set of about 500 time series, consisting of German data as well as data from Euro-area and G7 countries. For factor estimation, we consider standard...

We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many...

Multi-step-ahead forecasts of forecast uncertainty in practice are often based on the horizon-specific sample means of recent squared forecast errors, where the number of available past forecast errors decreases one-to-one with the forecast horizon. In this paper, the efficiency gains from the...

This paper explores the applicability of static and dynamic models to capture the stylized facts of exchange-rate dynamics. The static models (mixture of distributions, compound Poisson process, generalized Student distribution) are compatible with leptokurtosis and can be characterized as...

This paper evaluates the profitability of applying four different volatility forecasting models to the trading of straddles on the German stock market index DAX. Special care has been taken to use simultaneous intra-day prices and realistic transaction costs. Furthermore, straddle positions were...

This paper uses monthly survey data for the G7 countries for the time period 1989 - 2007 to explore the link between expectations on nominal wages, prices and unemployment rate as suggested by the traditional and Samuelson-and-Solow-type Phillips curve. Three major findings stand out: First, we...

Ziel der Analyse ist die Kurzfristprognose des deutsche (seewärtigen) Containerumschlags für Deutschland insgesamt, seine wichtigsten Fahrtgebiete (Europa, Asien, Nordamerika) und für den wichtigsen deutschen Seehafen Hamburg. Methodischer Ansatz ist ein SARIMA-Modell, dessen vorläufige...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting...