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...

This study presents a survey on the current methodologies employed in the asset allocation industry. We review techniques from Modern Portfolio Theory and focus on the central role of the mean-variance optimization problem. The formalism of the Black-Litterman model is discussed with its...

The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases,...

The intuitiveness and practicability of mean-variance portfolios largely depends on the accuracy of moment estimates, which are subject to large estimation errors and conditional on time. We propose a model accounting for factor dynamics in a Bayesian setting, in which the impact of estimation...

The performance of dynamic trading and investment strategies can be difficult to predict. Although not without its problems, analysis of the historical performance of a strategy can provide valuable insight into its general risk and return properties. Furthermore, historical analysis allows one...

It is now an accepted fact that the majority of financial markets worldwide are neither normal nor constant, and South Africa is no exception. One idea that can be used to understand such markets and has been gaining popularity recently is that of regimes and regime-switching models. In this...

One of the most important factors to control for the achievements of investment portfolio returns is risk. If we only think that a 100% positive return is needed to recover a portfolio loss of 50%, we can understand why. With the advent of the exponential growth of technology usage in markets,...

Transaction cost variance introduces a risk often neglected in portfolio optimization. We define a mean-variance portfolio optimization problem and show that including a transaction cost variance term significantly impacts the performance of these portfolios. Transaction cost variance is...

We develop a method to identify the most important predictors of long-term asset returns and use it to analyze the impact of model uncertainty on long-term investors. We find that the impact of model uncertainty changes a lot over time which leads to considerable time-variation in all moments of...