Portfolio Selection with Robust Estimation Victor DeMiguel Department of Management Science and Operations, London Business School, Regent’s Park, London NW1 4SA, UK, [email protected], http://faculty.london.edu/avmiguel/ Francisco J. Nogales Department of Statistics, Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911-Leganés (Madrid), Spain, [email protected], http:/...

Portfolio selection problem deals with how to form a satisfying portfolio, taking into account the uncertainty involved in the behavior of the financial markets. Markowitz (1952) established the relationship between the mean and variance of the investment in the framework of risk-return trade-off. Since then a variety of enlarged and improved models have been developed in several directions. So...

We propose a method for optimal portfolio selection using a Bayesian framework that addresses two major shortcomings of the Markowitz approach: the ability to handle higher moments and estimation error. We employ the skew normal distribution which has many attractive features for modeling multivariate returns. Our results suggest that it is important to incorporate higher order moments in portf...

There is a variety of models for portfolio selection. However, in portfolio theory applications little or no attention is paid to the cardinality problem. In this paper, an algorithm for dealing with this problem is presented. The proposed allocation algorithm is implemented in a software system, which is based on the Fuzzy Logic Q-measure Model and manages financial investments in real time. T...

We consider the problem of sequential portfolio selection in the stock market. There are theoretically well grounded algorithms for the problem, such as Universal Portfolio (UP), Exponentiated Gradient (EG) and Online Newton Step (ONS). Such algorithms enjoy the property of being universal, i.e., having low regret with the best constant rebalanced portfolio. However, the practical performance o...