Business investment is a very important variable for short- and medium-term economic analysis, but it is volatile and difficult to predict. Qualitative business survey data are widely used to provide indicators of economic activity ahead of the publication of official data. Traditional...

In this paper, we exploit the heterogeneity in the forecasts obtained by estimating different factor models to measure forecast uncertainty. Our approach is simple and intuitive. It consists first in selecting all the models that outperform some benchmark model, and then in constructing an...

We present a mixed-frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real-time is compared...

In this paper we develop a portfolio optimization strategy based on the extraction of option-implied distributions and the application of robust asset allocation. We compute the option-implied probability density functions of the constituents of the Euro Stoxx 50 Index. To obtain the...

We develop a dynamic multivariate default model for a portfolio of credit-risky assets in which default times are modelled as random variables with possibly different marginal distributions, and L�vy subordinators are used to model the dependence among default times. In particular, we...

In dynamic panel data models, which are particularly well-suited to cross-country analysis, the Mean Group estimator (Pesaran and Smith, 1995) is under certain quite strong conditions consistent, but theoretical and empirical evidence indicates that it can be biased when the number of time...

The paper examines the evolution of consumer confidence indices in Australia, Canada, France, Germany, Italy, Japan, the United Kingdom and the United States of America since the 1970s, by modelling them in a multivariate framework of common macroeconomic variables for each country. Results...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

In this paper we explore the performance of bridge and factor models in forecasting quarterly aggregates in the very short-term subject to a pre-selection of monthly indicators. Starting from a large information set, we select a subset of targeted predictors using data reduction techniques as in...

The size and power properties of several tests of equal Mean Square Prediction Error (MSPE) and of Forecast Encompassing (FE) are evaluated, using Monte Carlo simulations, in the context of dynamic regressions. For nested models, the F-type test of forecast encompassing proposed by Clark and...