We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

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 Component Analysis to higher moments such as skewness and...

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...

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...

In this paper, we use a database consisting of daily stock-returns for 20 countries to test for similarities between the left and right tail of returns as well as for cross-sectional differences. To mitigate the issue of dependency between stock returns, we estimate the distribution of extremes...

Our paper addresses the correction of the aggregation bias in linear rational expectations models when there is some unobserved micro-parameter heterogeneity and only macro data are available. Starting from Lewbel (1994), we propose two new consistent estimators, which rely on a flexible...

Many macroeconomic models (including the NKPC - "New Keynesian" Phillips Curve) involve hybrid equations, in which some variables depend on both their lags and leads. Hybrid models have produced conflicting empirical results: GMM (respectively ML) estimation find the forward- looking component...