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An interior point algorithm for large scale portfolio optimization

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Abstract

The minimum-norm point problem which arises in portfolio selections is discussed and an interior point algorithm to solve the problem is proposed in this paper. Three kinds of problems, the mean-variance, the index matching and the multiple factor models are viewed as variants of the minimum-norm point problem. Results of the computational experiments are attached to show the proposed algorithm as a very powerful tool for large scale portfolio optimization.

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Authors and Affiliations

  1. MTB Investment Technology Institute, Co., Ltd, Nihon Bldg, 2-6-2 Ohtemachi, Chiyoda-ku, 100, Tokyo, Japan

    Hitoshi Takehara

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  1. Hitoshi Takehara
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Revised version of “On the minimum-norm point problem in portfolio selections”.

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Takehara, H. An interior point algorithm for large scale portfolio optimization. Ann Oper Res 45, 373–386 (1993). https://doi.org/10.1007/BF02282059

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