This paper systematically studies the use of mixed-frequency data sets and suggests that the use of high frequency data in forecasting economic aggregates can improve forecast accuracy. The best way of using this information is to build a single model, for example, an ARMA model with missing...

Der vorliegende Beitrag zeigt verschiedene Möglichkeiten auf, um repräsentative Renditen für die Anlageklasse Immobilien berechnen zu können. Betrachtet werden Indizes auf der Basis (i) von regelmäßig bewerteter Immobilienportefeuilles, (ii) auf Basis von Markttransaktionen in Immobilien...

The Recent crises have seen very large spikes in asset price risk without dramatic shifts in fundamentals. We propose an explanation for these risk panics based on self-fulfilling shifts in risk made possible by a negative link between the current asset price and risk about the future asset...

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between...

I present empirical results on the contribution of three key drivers of inflation in Denmark: an inflation trend anchored by inflation expectations; the Danish business cycle; and an energy price cycle. All three drivers contribute significantly to the development of inflation and explain most of...

Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...