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. …

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 …

pricing kernel with all underlying risk factors, we decompose the expected stock return into four risk premiums related to the …

"Systematic Downside Risk" (SDR) is defined to characterize this asymmetry in the comovement of betas. This indicator negatively …

investment’s effectiveness and risk. At first, we give an overview of various methods of bootstrap confidence interval estimation …

Dependence modelling and estimation is a key issue in the assessment of portfolio risk. When measuring extreme risk in … terms of the Value-at-Risk, the multivariate normal model with linear correlation as its natural dependence measure is by no … the data. -- Risk management ; extreme risk assessment ; multivariate models ; dependence function …