In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate GARCH-type specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only avoids the...

This paper documents the existence of large structural breaks in the unconditional correlations among the British pound, Norwegian krone, Swedish krona, Swiss franc, and euro exchange rates (against the US dollar) during the period 1994-2003. Using the framework of dynamic conditional...

Managers have the choice to take the firm private themselves in a management buy-out or to seek private equity backing. We argue that managers seek private equity backing in case they are more constrained to finance the deal themselves. We confirm the hypothesis using a sample of UK...

Over the last decade, the going private market has experienced a considerable boom in size and also has become more interesting for private equity investors that are looking to partner with incumbent management. This offers managers the choice to take the firm private themselves in a traditional...

The accuracy of real-time forecasts of macroeconomic variables that are subject to revisions may crucially depend on the choice of data used to compare the forecasts against. We put forward a flexible time - varying parameter regression framework to obtain early estimates of the final value of...

This paper develops a return forecasting methodology that allows for instability in the relationship between stock returns and predictor variables, for model uncertainty, and for parameter estimation uncertainty. The predictive regression specification that is put forward allows for occasional...

We assess the relevance of parameter uncertainty, model uncertainty, and macroeconomic information for forecasting the term structure of interest rates. We study parameter uncertainty by comparing Bayesian inference with frequentist estimation techniques, and model uncertainty by combining...

We develop new multi-factor dynamic copula models with time-varying factor loadings and observation-driven dynamics. The new models are highly flexible, scalable to high dimensions, and ensure positivity of covariance and correlation matrices. A closed-form likelihood expression allows for...

We investigate the effect of estimation error on backtests of (multi-period) expected shortfall (ES) forecasts. These backtests are based on first order conditions of a recently introduced family of jointly consistent loss functions for Value-at-Risk (VaR) and ES. We provide explicit expressions...

The dynamic factor Markov-switching (DFMS) model introduced by Diebold and Rudebusch (1996) has proven to be a powerful framework to measure the business cycle. We extend the DFMS model by allowing for time-varying transition probabilities, with the aim of accelerating the real-time dating of...