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A portfolio optimization model for minimizing soft margin-based generalization bound

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Abstract

Roy’s safety first (RSF) criterion aims to minimize the shortfall probability in portfolio selection. Smoothed safety first portfolio optimization model is a useful tool to realize RSF criterion by minimizing an approximation of the empirical shortfall probability. However, the generalization performance of the smoothed safety first portfolio optimization model may be poor when the number of the samples is finite. In this paper, a soft margin-based generalization bound on the shortfall probability is obtained firstly. Then, a portfolio optimization model is built by minimizing the soft margin-based generalization bound. Finally, the good generalization performance of the portfolio optimization model is verified by experiments.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Nos. 60773062, 61073121), the Natural Science Foundation of Hebei Province of China (Nos. F2012402037, A2012201033).

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Authors and Affiliations

  1. College of Management, Hebei University, Baoding, 071002, China

    Minghu Ha & Yang Yang

  2. School of Economics and Management, Hebei University of Engineering, Handan, 056038, China

    Minghu Ha & Chao Wang

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  1. Minghu Ha
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  2. Yang Yang
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  3. Chao Wang
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Correspondence to Minghu Ha.

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Ha, M., Yang, Y. & Wang, C. A portfolio optimization model for minimizing soft margin-based generalization bound. J Intell Manuf 28, 759–766 (2017). https://doi.org/10.1007/s10845-014-1011-7

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  • DOI: https://doi.org/10.1007/s10845-014-1011-7

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