A hybrid optimization approach to index tracking

Rubén Ruiz-Torrubiano () and Alberto Suárez ()

Annals of Operations Research, 2009, vol. 166, issue 1, 57-71

Abstract: Index tracking consists in reproducing the performance of a stock-market index by investing in a subset of the stocks included in the index. A hybrid strategy that combines an evolutionary algorithm with quadratic programming is designed to solve this NP-hard problem: Given a subset of assets, quadratic programming yields the optimal tracking portfolio that invests only in the selected assets. The combinatorial problem of identifying the appropriate assets is solved by a genetic algorithm that uses the output of the quadratic optimization as fitness function. This hybrid approach allows the identification of quasi-optimal tracking portfolios at a reduced computational cost. Copyright Springer Science+Business Media, LLC 2009

Keywords: Data mining; Financial modeling; Asset management (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (17)

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DOI: 10.1007/s10479-008-0404-4

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