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Kernel Search: An application to the index tracking problem

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  • Guastaroba, G.
  • Speranza, M.G.

Abstract

In this paper we study the problem of replicating the performances of a stock market index, i.e. the so-called index tracking problem, and the problem of out-performing a market index, i.e. the so-called enhanced index tracking problem. We introduce mixed-integer linear programming (MILP) formulations for these two problems. Furthermore, we present a heuristic framework called Kernel Search. We analyze and evaluate the behavior of several implementations of the Kernel Search framework to the solution of the index tracking problem. We show the effectiveness and efficiency of the framework comparing the performances of these heuristics with those of a general-purpose solver. The computational experiments are carried out using benchmark and newly created instances.

Suggested Citation

  • Guastaroba, G. & Speranza, M.G., 2012. "Kernel Search: An application to the index tracking problem," European Journal of Operational Research, Elsevier, vol. 217(1), pages 54-68.
    • Handle: RePEc:eee:ejores:v:217:y:2012:i:1:p:54-68
    DOI: 10.1016/j.ejor.2011.09.004
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    References listed on IDEAS

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