The Markowitz mean-variance optimization model is a widely used tool for portfolio selection. However, in order to capture real world restrictions on actual investments, a Limited Asset Markowitz (LAM) model with the introduction of quantity and cardinality constraints has been considered. These two constraints have been modelled by adding binary variables to the Markowitz model, thus resulting...

The Markowitz mean-variance optimization model is a widely used tool for portfolio selection. However, in order to capture real world restrictions on actual investments, a Limited Asset Markowitz (LAM) model with the introduction of quantity and cardinality constraints has been considered. These two constraints have been modelled by adding binary variables to the Markowitz model, thus resulting...

A number of variants of the classical Markowitz mean-variance optimization model for portfolio selection have been investigated to render it more realistic. Recently, it has been studied the imposition of a cardinality constraint, setting an upper bound on the number of active positions taken in the portfolio, in an attempt to improve its performance and reduce transactions costs. However, one ...

It is a matter of common knowledge that traditional Markowitz optimization based on sample means and covariances performs poorly in practice. For this reason, diverse attempts were made to improve performance of portfolio optimization. In this paper, we investigate three popular portfolio selection models built upon classical meanvariance theory. The first model is an extension of the tradition...

Abstract. Portfolio theory deals with the question of how to allocate resources among several competing alternatives (stocks, bonds), many of which have an unknown outcome. In this paper we provide an overview of different portfolio models with emphasis on the corresponding optimization problems. For the classical Markowitz mean-variance model we present computational results, applying a dual a...

Departure from normality poses implementation barriers to the Markowitz mean-variance portfolio selection. When assets are affected by common and idiosyncratic shocks, the distribution of asset returns may exhibit Markov switching regimes and have a Gaussian mixture distribution conditional on each regime. The model is estimated in a Bayesian framework using the Gibbs sampler. An application to...

n this paper the problem of capacity planning under risk from demand and price/cost uncertainty of the finished products is addressed. The deterministic model is extended into a two-stage stochastic model with fixed recourse by means of various expected levels of demand as random. A recourse penalty is also included in the objective for both shortage and surplus in the finished products. The mo...

Introduction One of the basic problems of applied finance is the optimal selection of stocks by conflicting objective of maximizing future return and minimizing investment risk. The first systematic treatment of this dilemma is the mean variance approach proposed by Markowitz. Markowitz combined the optimization and probability theory to solve the dilemma. In Markowitz’s mean variance model, th...

This paper describes the application of a simulated annealing approach to the solution of a complex portfolio selection model. The model is a mixed integer quadratic programming problem which arises when Markowitz classical mean–variance model is enriched with additional realistic constraints. Exact optimization algorithms run into difficulties in this framework and this motivates the investiga...