This paper studies vector autoregressive models with parsimoniously time-varying parameters. The parameters are assumed to follow parsimonious random walks, where parsimony stems from the assumption that increments to the parameters have a non-zero probability of being exactly equal to zero. We...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

Cyclicality in the losses of bank loans is important for bank risk management. Because loans have a different risk profile than bonds, evidence of cyclicality in bond losses need not apply to loans. Based on unique data we show that the default rate and loss given default of bank loans share a...

We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for...

This discussion paper resulted in an article in the <I>Oxford Bulletin of Economics and Statistics</I> (2008). Vol. 70 issue 1, pages 23-51.<P> This paper investigates business cycle relations among different economies in theEuro area. Cyclical dynamics are explicitly modelled as part of a time series...</p></i>

This paper proposes the use of a double correlation coefficient as a nonpara- metric measure of phase-dependence in time-varying correlations. An asymp- totically Gaussian test statistic for the null hypothesis of no phase-dependence is derived from the proposed measure. Finite-sample...