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Construction of Emerging Markets Exchange Traded Funds Using Multiobjective Particle Swarm Optimisation

  • Marta Díez-Fernández
  • Sergio Alvarez Teleña
  • Denise Gorse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7553)

Abstract

Multiobjective particle swarm optimisation (MOPSO) techniques are used to implement a new Andean stock index as an exchange traded fund (ETF) with weightings adjusted to allow for a tradeoff between the minimisation of tracking error, and liquidity enhancement by the reduction of transaction costs and market impact. Solutions obtained by vector evaluated PSO (VEPSO) are compared with those obtained by the quantum-behaved version of this algorithm (VEQPSO) and it is found the best strategy for a portfolio manager would be to use a hybrid front with contributions from both versions of the MOPSO algorithm.

Keywords

Multiobjective optimisation particle swarm optimisation portfolio management emerging markets 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marta Díez-Fernández
    • 1
  • Sergio Alvarez Teleña
    • 1
  • Denise Gorse
    • 1
  1. 1.Dept of Computer ScienceUniversity College LondonLondonUK

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