Economics at your fingertips  

Fast Quadratic Programming for Mean-Variance Portfolio Optimisation

Vasileios E. Kontosakos ()
Additional contact information
Vasileios E. Kontosakos: Monash University

SN Operations Research Forum, 2020, vol. 1, issue 3, 1-15

Abstract: Abstract In this paper, a vectorised quadratic convex optimisation algorithm based on Matlab’s quadprog built-in function is proposed. We target specifically a classic problem confronted by portfolio analysts, that of optimising asset allocation when choosing among several asset classes, in the context of Markowitz’s modern portfolio theory. Simulating return trajectories for several asset classes, we formulate the optimisation routine in such a way that is able to handle multiple scenarios at the same time, instead of on a one-by-one basis, reducing computational times significantly, without introducing observable estimation errors. A sensitivity analysis is offered with respect to the optimal batch size.

Keywords: Quadratic programming; Vectorisation; Portfolio optimisation; Algorithmic efficiency (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) 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:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s43069-020-00025-0

Access Statistics for this article

SN Operations Research Forum is currently edited by Marco Lübbecke

More articles in SN Operations Research Forum from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2020-10-07
Handle: RePEc:spr:snopef:v:1:y:2020:i:3:d:10.1007_s43069-020-00025-0