We propose new methods for evaluating predictive densities. The methods include Kolmogorov-Smirnov and Cramér-von Mises-type tests for the correct specification of predic[...]

We propose a new methodology to identify the sources of models' forecasting performance. The methodology decomposes the models' forecasting performance into asymptoticall[...]

This paper provides evidence of the quality of private sector forecasts of the budget balance between 1993 and 2009 for a sample of 29 countries, grouped into advanced an[...]

We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of lagged volatility, lagged[...]

The answer depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and[...]

Information on the allocation and pricing of over-the-counter (OTC) markets is scarce. Furfine (1999) pioneered an algorithm that provides transaction-level data on the O[...]

Increased sovereign credit risk is often associated with sharp currency movements. Therefore, expectations of the probability of a sovereign default event can convey impo[...]

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empi[...]

Forecast combinations, also known as ensemble models, routinely require practitioners to select a model from a massive number of potential candidates. Ten explanatory var[...]

This paper studies tail risk and its option-implied risk compensation in the crude oil market. We identify economically large premia for upside and downside tail risks th[...]