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A nonparametric approach to portfolio shrinkage

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  • Han, Chulwoo

Abstract

This paper develops a shrinkage model for portfolio choice. It places a layer on a conventional portfolio problem where the optimal portfolio is shrunk towards a reference portfolio. The model can accommodate a wide range of portfolio problems with various objectives and constraints, and its implementation is simple and straightforward. A data-driven method to determine the shrinkage level is offered. A comprehensive comparative study suggests the proposed model substantially enhances the performance of its underlying model and outperforms existing shrinkage models as well as the naïve strategy. The naïve strategy serves better as the reference portfolio than the current portfolio.

Suggested Citation

  • Han, Chulwoo, 2020. "A nonparametric approach to portfolio shrinkage," Journal of Banking & Finance, Elsevier, vol. 120(C).
    • Handle: RePEc:eee:jbfina:v:120:y:2020:i:c:s0378426620302156
    DOI: 10.1016/j.jbankfin.2020.105953
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    Cited by:

    1. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.

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    More about this item

    Keywords

    Turnover minimization; Shrinkage estimator; Parameter uncertainty; Portfolio optimization;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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