We use a comprehensive dataset of Funds-of-Hedge-Funds (FoFs) to investigate performance, risk and capital formation in the hedge fund industry over the past ten years. We confirm the finding of high systematic risk exposures in FoF returns. We divide up the past ten years into three distinct...

This paper presents ideas and methods underlying the construction of an indicator that tracks euro area GDP growth but, unlike GDP growth, (i) is updated monthly and almost in real time, and (ii) is free from short-run dynamics. Removal of short-run dynamics from a time series to isolate the...

We explore whether forecasting an aggregate variable using information on its disaggregate components can improve the prediction mean squared error over first forecasting the disaggregates and then aggregating those forecasts, or, alternatively, over using only lagged aggregate information in...

We investigate the presence of significant electricity forward risk premia, using data from three major continental European energy markets - German, Dutch and French. We introduce the risk premium in the framework of a standard electricity spot/forward unobserved factor model, and derive the...

This paper provides a semiparametric framework for modeling multivariate conditional heteroskedasticity. We put forward latent stochastic volatility (SV) factors as capturing the commonality in the joint conditional variance matrix of asset returns. This approach is in line with common features...

This paper proposes a high dimensional factor multivariate stochastic volatility (MSV) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in...