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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...
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 conditional...
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 portfolio allocation. Also, structural...
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: <p> -with what frequency do we find variations...</p>
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...