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Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics

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  • Caldeira, João F.
  • Santos, André A.P.
  • Torrent, Hudson S.

Abstract

Empirical evidence shows that the relationship between firm characteristics and stock returns is non-linear, with a stronger correlation at the extreme deciles of the characteristic values. In this paper, we propose a novel portfolio optimization method that models the portfolio weights as a non-linear function of firm characteristics. Our approach allows the weights to vary non-linearly across percentiles of the cross-sectional distribution of each characteristic. We apply our method to the universe of firms listed in the NYSE, AMEX, and NASDAQ and find that non-linear effects in size, value, and momentum anomalies are important for constructing portfolios that have lower risk and higher risk-adjusted returns. Our results suggest that a flexible relation between portfolio weights and firm characteristics can better capture the empirical patterns observed in the data.

Suggested Citation

  • Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    • Handle: RePEc:eee:ecmode:v:122:y:2023:i:c:s0264999323000512
    DOI: 10.1016/j.econmod.2023.106239
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    References listed on IDEAS

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    More about this item

    Keywords

    Penalized splines; Portfolio turnover; Sharpe ratios;
    All these keywords.

    JEL classification:

    • B26 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Financial Economics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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