The book provides deep insights into the signal extraction problem - especially at the boundary of a sample, where asymmetric filters must be used - and how to solve it optimally. The traditional model-based approach (TRAMO/SEATS or X-12-ARIMA) is an inefficient estimation method because it...

This book reviews forecasting data mining models, from basic tools for stable data through causal models, to more advanced models using trends and cycles. These models are demonstrated on the basis of business-related data, including stock indices, crude oil prices, and the price of gold. The...

Despite powerful advances in yield curve modeling in the last twenty years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the no-arbitrage approach, which focuses on accurately fitting the cross...

In diesem Beitrag wird analysiert, ob Wechselkursprognosen Anhaltspunkte dafür liefern, dass Prognostiker ein so genanntes Herdenverhalten zeigen. Auf der Basis unterschiedlicher theoretischer Modellansätze wird skizziert, warum Prognostiker einen Anreiz haben könnten, einem Herdentrieb zu...

Business cycles reflect changes over time in the amount of trade between individuals. In this paper we show that incorporating explicitly intra-temporal gains from trade between individuals into a macroeconomic model can provide new insight into the potential mechanisms driving economic...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...