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Portfolio Optimisation with Cap Weight Restrictions

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Decision Technologies for Computational Finance

Part of the book series: Advances in Computational Management Science ((AICM,volume 2))

Abstract

The practical application of the Markowitz portfolio optimisation framework faces the problem of noise when historical estimates are used as input parameters. In this paper I propose a simple modification for portfolio optimisation that allows for the incorporation of a priori information in the portfolio optimisation process. Capital market theory and empirical results indicate that capitalisation weights are a reasonable source of information. The modified framework can be interpreted as an approach to practical portfolio optimisation, which refers to the Bayesian principle of using prior information in decision making under uncertainty.

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© 1998 Springer Science+Business Media Dordrecht

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Wagner, N.F. (1998). Portfolio Optimisation with Cap Weight Restrictions. In: Refenes, AP.N., Burgess, A.N., Moody, J.E. (eds) Decision Technologies for Computational Finance. Advances in Computational Management Science, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5625-1_32

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  • DOI: https://doi.org/10.1007/978-1-4615-5625-1_32

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-8309-3

  • Online ISBN: 978-1-4615-5625-1

  • eBook Packages: Springer Book Archive

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