We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model …

and risk features than very simple and very complex models. Combinations of two strategies help, in particular, to reduce … risk features like volatility and largest loss, which indicates that complete densities provide useful information for risk …

and risk features than very simple and very complex models. Combinations of two strategies help, in particular, to reduce … risk features like volatility and largest loss, which indicates that complete densities provide useful information for risk. …

A model of portfolio return dynamics is considered in which the price of risk is permitted to be heterogeneous. In … innovation is the use of a set of predictors that account for variation in risk prices across (segmented) markets. These … competing methods (including those that assume homogeneous risk prices) when applied to domestic and international data -- a …

climate mitigation, and the direction of the risk is identified through manual labels. The documented risk premium indicates …

about estimation risk in FFMs in high dimensions. We investigate whether recent linear and non-linear shrinkage methods help … to reduce the estimation risk in the asset return covariance matrix. Our findings indicate that modest improvements are …

We examine the pricing of tail risk in international stock markets. We find that the tail risk of different countries … mainly driven by global tail risk rather than local tail risk. World fear is also priced in the crosssection of stock returns …