An application of Microsoft Excel's evolutionary solver based on a novel chromosome encoding scheme to the 1/N portfolio tracking problem

Strub, Oliver; Trautmann, Norbert (2016). An application of Microsoft Excel's evolutionary solver based on a novel chromosome encoding scheme to the 1/N portfolio tracking problem. In: 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 745-749). IEEE 10.1109/IEEM.2016.7797975

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The 1/N portfolio is an equally-weighted portfolio composed of all N stocks from a given investment universe. This portfolio offers an attractive risk-return profile but causes substantial management costs if N is large. Therefore, we consider the problem of optimally tracking the 1/N portfolio by constructing an equally-weighted portfolio composed of a subset of the N stocks. This problem can be formulated as a binary quadratic program that, however, becomes computationally expensive to solve for mathematical programming solvers if N is large. In this paper, we present a novel chromosome encoding scheme based on a string of unique integers representing the indices of the selected stocks. We implement this scheme on a spreadsheet and apply Microsoft Excel's evolutionary solver to devise tracking portfolios. We demonstrate that, by using our novel encoding scheme instead of an existing one, the solver determines considerably better solutions.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Financial Management > Professorship for Quantitative Methods in Business Administration

UniBE Contributor:

Strub, Oliver, Trautmann, Norbert

Subjects:

600 Technology > 650 Management & public relations

ISBN:

978-1-5090-3665-3

Publisher:

IEEE

Language:

English

Submitter:

Juliana Kathrin Moser-Zurbrügg

Date Deposited:

07 Jul 2017 15:46

Last Modified:

05 Dec 2022 15:02

Publisher DOI:

10.1109/IEEM.2016.7797975

BORIS DOI:

10.7892/boris.94980

URI:

https://boris.unibe.ch/id/eprint/94980

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