EconPapers    
Economics at your fingertips  
 

Solving cardinality constrained mean-variance portfolio problems via MILP

Nasim Dehghan Hardoroudi, Abolfazl Keshvari (), Markku Kallio and Pekka Korhonen
Additional contact information
Nasim Dehghan Hardoroudi: Aalto University School of Business
Abolfazl Keshvari: Aalto University School of Business
Markku Kallio: Aalto University School of Business

Annals of Operations Research, 2017, vol. 254, issue 1, 47-59

Abstract: Abstract Controlling the number of active assets (cardinality of the portfolio) in a mean-variance portfolio problem is practically important but computationally demanding. Such task is ordinarily a mixed integer quadratic programming (MIQP) problem. We propose a novel approach to reformulate the problem as a mixed integer linear programming (MILP) problem for which computer codes are readily available. For numerical tests, we find cardinality constrained minimum variance portfolios of stocks in S&P500. A significant gain in robustness and computational effort by our MILP approach relative to MIQP is reported. Similarly, our MILP approach also competes favorably against cardinality constrained portfolio optimization with risk measures CVaR and MASD. For illustrations, we depict portfolios in a portfolio map where cardinality provides a third criterion in addition to risk and return. Fast solution allows an interactive search for a desired portfolio.

Keywords: Portfolio optimization; Cardinality constraints; Mean-variance theory; CVaR; MASD; MILP (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s10479-017-2447-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2447-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2019-05-26
Handle: RePEc:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2447-x