Lexicographic and weighting approach to multi-criteria portfolio optimization by mixed integer programming

Bartosz Sawik

doi:10.1108/S0276-8976(2009)0000013003

Login

Welcome:
Guest

Search for:

Browse:

Product Information:

Resources:

Applications of Management Science

ISSN: 0276-8976
Series editor(s): Professor Kenneth D. Lawrence

Subject Area: Management Science/Management Studies

Content: Series Volumes | Current Volume RSS

Options: To add Favourites and Table of Contents Alerts please take a Emerald profile

Document request:
Lexicographic and weighting approach to multi-criteria portfolio optimization by mixed integer programming

Document Information:
Title:	Lexicographic and weighting approach to multi-criteria portfolio optimization by mixed integer programming
Author(s):	Bartosz Sawik
Volume:	13 Editor(s): Kenneth D. Lawrence, Gary Kleinman ISBN: 978-1-84855-878-6 eISBN: 978-1-84855-879-3
Citation:	Bartosz Sawik (2009), Lexicographic and weighting approach to multi-criteria portfolio optimization by mixed integer programming, in Kenneth D. Lawrence, Gary Kleinman (ed.) Financial Modeling Applications and Data Envelopment Applications (Applications of Management Science, Volume 13), Emerald Group Publishing Limited, pp.3-18
DOI:	10.1108/S0276-8976(2009)0000013003 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	This chapter presents the portfolio optimization problem formulated as a multi-criteria mixed integer program. Weighting and lexicographic approach are proposed. The portfolio selection problem considered is based on a single-period model of investment. An extension of the Markowitz portfolio optimization model is considered, in which the variance has been replaced with the Value-at-Risk (VaR). The VaR is a quantile of the return distribution function. In the classical Markowitz approach, future returns are random variables controlled by such parameters as the portfolio efficiency, which is measured by the expectation, whereas risk is calculated by the standard deviation. As a result, the classical problem is formulated as a quadratic program with continuous variables and some side constraints. The objective of the problem considered in this chapter is to allocate wealth on different securities to maximize the weighted difference of the portfolio expected return and the threshold of the probability that the return is less than a required level. The auxiliary objectives are minimization of risk probability of portfolio loss and minimization of the number of security types in portfolio. The four types of decision variables are introduced in the model: a continuous wealth allocation variable that represents the percentage of wealth allocated to each asset, a continuous variable that prevents the probability that return of investment is not less than required level, a binary selection variable that prevents the choice of portfolios whose VaR is below the minimized threshold, and a binary selection variable that represents choice of stocks in which capital should be invested. The results of some computational experiments with the mixed integer programming approach modeled on a real data from the Warsaw Stock Exchange are reported.