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...

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...

The aim of this paper is to compare various methods which extract a Risk Neutral Density (RND) out of PIBOR as well as of Notional interest rate futures options and to investigate how traders reacted to a political event. We first focus on 5 dates surrounding the 1997 snap election and several...

For central banks, institutional, and individual investors, it is crucial to understand the frequency and importance of drops or sudden rises in financial markets. Extreme value theory (EVT) is an interesting tool providing answers to questions such as: With what frequency do we find variations...

Recent portfolio choice asset pricing and option valuation models highlight the importance of skewness and kurtosis. Since skewness and kurtosis are related to extreme variations they are also important for Value-at-Risk measurements. Our framework builds on a GARCH model with a condi-tional...

The entropy principle yields, for a given set of moments, a density that involves the smallest amount of prior information,. We first show how entropy densities may be constructed in a numerically efficient way as the minimization of a potential. Next, for the case where the first four moments...

We develop a new methodology that measures conditional dependency. We achieve this by using copula functions that link marginal distributions, here chosen to obey a GARCH-type model with time-varying skewness and kurtosis. We apply this model to daily returns of stock-market indices. We find...

Designing an investment strategy in transition economies is a difficult task, because stock markets opened through time, time series are short, and there is little guidance how to obtain expected returns and covariance matrices necessary for mean-variance asset allocation. Moments of market...