This paper developes a new methodology to measure conditional dependency between time series each driven by complicated marginal distributions.

We evaluate how deviations from normality may affect the allocation of assets. A Taylor expansion of expected utility allows us to focus on certain moments and to compute numerically the optimal portfolio allocation. A decisive advantage of our approach is that it remains operational even if a...

It is well known that strategies that allow investors to allocate their wealth using return and volatility forecasts, the use of which are termed market and volatility timing, are of significant value. In this paper, we show that distribution timing, defined here as the ability to use forecasts...

We evaluate how non-normality of asset returns and the temporal evolution of volatility and higher moments affects the conditional allocation of wealth. We show that if one neglects these aspects, as would be the case in a mean-variance allocation, a significant cost would arise. The performance...

In this paper, we extend the concept of News Impact Curve developed by Engle and Ng (1993) to the higher moments of the multivariate returns' distribution, thereby providing a tool to investigate the impact of shocks on the characteristics of the subsequent distribution. For this purpose, we...

It is well known that non-normality plays an important role in asset and risk management.However, handling a large number of assets has long been a challenge.In this paper, we present a statistical technique that extends Principal ComponentAnalysis to higher moments such as skewness and...

We implement a long-horizon static and dynamic portfolio allocation involvinga risk-free and a risky asset. This model is calibrated at a quarterly frequencyfor ten European countries. We also use maximum-likelihood estimates andBayesian estimates to account for parameter uncertainty. We nd that...

In this paper, we extend the concept of the news impact curve of volatility developed by Engle and Ng (1993) to the higher moments and co-moments of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model with non-normal innovations. For this purpose, we present...

In this study we compare the quality and information content of risk neutral densities obtained by various methods. We consider a non-structural method, based on a mixture of log-normal densities, and the semi-nonparametric ones, based on an Hermite approximation of Abken, Madan, Milne, and...