We propose to estimate heteroskedastic dynamic factor models using the Kalman filter, where the state vector is augmented with the heteroskedastic disturbances. Although this model is not conditionally Gaussian, Monte Carlo results show that parameters can be accurately estimated.

We develop a new dynamic factor model that allows us to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers...

We develop a new dynamic factor model that allows us to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers...

We develop a new dynamic factor model that allows us to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers...

We develop a new dynamic factor model that allows us to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers...

Equity basket correlation is an important risk factor. It characterizes the strength of linear dependence between assets and thus measures the degree of portfolio diversification. It can be estimated both under the physical measure from return series, and under the risk neutral measure from...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...

Real-time macroeconomic data refl ect the information available to market participants, whereas fi nal data-containing revisions and released with a delay-overstate the information set available to them. We document that the in-sample and out-of-sample Treasury return predictability is signifi...

Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...