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A constrained cluster-based approach for tracking the S&P 500 index
University of Toronto, Canada.
University of Toronto, Canada.
University of Toronto, Canada.
2017 (English)In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 193, p. 222-243Article in journal (Refereed) Published
Abstract [en]

We consider the problem of tracking a benchmark target portfolio of financial securities in particular the S&P 500. Linear integer programming models are developed that seeks to track a target portfolio using a strict subset of securities from the benchmark portfolio. The models represent a clustering approach to select securities and also include additional constraints that aim to control risk and transactions costs. Lagrangian and semi-Lagrangian methods are developed to compute solutions to the tracking models. The computational results show the effectiveness of the linear tracking models and the computational methods in tracking the S&P 500. Overall, the models and methods presented can serve as the basis of the optimization module in an optimization-based decision support for creating tracking portfolios.

Place, publisher, year, edition, pages
2017. Vol. 193, p. 222-243
Keywords [en]
Index tracking, Portfolio optimization, Linear mixed integer programming, Lagrangian relaxation
National Category
Business Administration
Identifiers
URN: urn:nbn:se:su:diva-152800DOI: 10.1016/j.ijpe.2017.07.018OAI: oai:DiVA.org:su-152800DiVA, id: diva2:1181122
Funder
Marianne and Marcus Wallenberg FoundationAvailable from: 2018-02-07 Created: 2018-02-07 Last updated: 2018-05-18Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf