In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a...

In this paper, we ask whether it is possible to forecast gross-value added (GVA) and its sectoral sub-components at the regional level. We are probably the first who evaluate sectoral forecasts at the regional level using a huge data set at quarterly frequency to investigate this issue. With an...

This paper investigates dynamic currency hedging benefits, with a further focus on the impact of currency hedging before and during the recent financial crises originated from the subprime and the Euro sovereign bonds. We take the point of view of a Euro-based institutional investor who...

We use factor augmented vector autoregressive models with time-varying coefficients to construct a financial conditions index. The time-variation in the parameters allows for the weights attached to each financial variable in the index to evolve over time. Furthermore, we develop methods for...

This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and...

We provide clear-cut evidence for economically and statistically significant multivariate jumps (multi-jumps) occurring simultaneously in stock prices by using a novel nonparametric test based on smoothed estimators of integrated variances. Detecting multi-jumps in a panel of liquid stocks is...

This paper considers forecast combination in a predictive regression. We construct the point forecast by combining predictions from all possible linear regression models given a set of potentially relevant predictors. We propose a frequentist model averaging criterion, an asymptotically unbiased...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

Complexity in the financial markets requires intelligent forecasting models for return volatility. In this paper, historical simulation, GARCH, GARCH with skewed student-t distribution and asymmetric normal mixture GRJ-GARCH models are combined with Extreme Value Theory Hill by using artificial...