It is well known that the portfolio optimization involves creating the stock portfolio minimizing the risk for a required return or maximizing the return for a given risk level. The mathematic model of these kind of problem is one of quadratic programming type. Because the solving procedure of...

This paper presents a new possibilistic programming approach to the portfolio selection problem. It is based on two issues: the approximation of the rates of return on securities by means of fuzzy numbers of trapezoidal form, for which we use the interval-valued ex-pectation defined by Dubois...

We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We propose and justify approaches based on simulation and the block bootstrap to achieve valid inference in a time series...

Enhanced Indexation is the problem of selecting a portfolio that should produce excess return with respect to a given benchmark index. In this work we propose a linear bi-objective optimization approach to Enhanced Indexation that maximizes average excess return and minimizes underperformance...

This study develops and implements a theory and method for analyzing whether introducing new securities or relaxing investment constraints improves the investment opportunity set for risk averse investors. We develop a test procedure for ‘stochastic spanning’ for two nested polyhedral...

Existing models in stochastic continuous-time settings assume that beliefs are represented by a probability measure. As illustrated by the Ellsberg Paradox, this feature rules out a priori any concern with ambiguity. This paper formulates a continuous-time intertemporal version of...

When ambiguity averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. As a result, they react more strongly to bad news than to good news. They also dislike assets for which information quality is poor, especially when the underlying...

This paper considers learning when the distinction between risk and ambiguity (Knightian uncertainty) matters. Working within the framework of recursive multiple-priors utility, the paper formulates a counterpart of the Bayesian model of learning about an uncertain parameter from conditionally...

When ambiguity averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. As a result, they react more strongly to bad news than to good news. They also dislike assets for which information quality is poor, especially when the underlying...

The Markowitz mean-variance optimizing framework has served as the basis for modern portfolio theory for more than 50 years. However, efforts to translate this theoretical foundation into a viable portfolio construction algorithm have been plagued by technical difficulties stemming from the...