Contributed Session Fri.1.H 3021

Friday, 10:30 - 12:00 h, Room: H 3021

Cluster 7: Finance & economics [...]

Portfolio selection problems


Chair: Marius Radulescu



Friday, 10:30 - 10:55 h, Room: H 3021, Talk 1

Constanta Zoie Radulescu
Portfolio selection models with complementarity constraints

Coauthors: Marius Radulescu, Sorin Radulescu


We extend Markowitz’s portfolio selection model to include transaction costs in the presence of initial holdings for the investor. Our approach is new. Our aim is to obtain an optimal portfolio which has a minimum risk or a maximum return. Our portfolio selection models include complementarity constraints. This type of constraints increases the difficulty of the problems, which now enter in the category of combinatorial optimization problems. The set of feasible solutions for the problems from the above mentioned class is the union of a set of convex sets but it is no longer convex. We give an algorithm for finding solutions of portfolio selection models with complementarity constraints. Several numerical results are discussed.



Friday, 11:00 - 11:25 h, Room: H 3021, Talk 2

Marius Radulescu
The efficient frontiers of mean-variance portfolio selection problems

Coauthors: Constanta Zoie Radulescu, Sorin Radulescu


In the paper are defined the notions of efficient frontier set and efficient frontier function of a parametric
optimization problem. We formulate several portfolio selection problems which are nonlinear programming problems. Two of them are minimum variance type problems and the other two are maximum expected return type problems. Taking into account various hypotheses on the covariance matrix and on the vector of means the duality between minimum variance type problems and maximum expected return type problems is investigated. We are interested when the efficient frontier sets of the minimum variance type problems and of the maximum expected return type problems are equal.
Generalization of the problems studied to the case of mean-risk models is suggested.


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