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Regression, multicollinearity and Markowitz

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  • Ortiz, Roberto
  • Contreras, Mauricio
  • Mellado, Cristhian

Abstract

This paper shows that the usual drawbacks of the Markowitz model (high optimal weights, high volatility and low out-of-sample performance) can be overcome by correcting for the multicollinearity of individual assets that directly affect the estimation of portfolio weights. That improves the stability, predictability and out-of-sample performance of the Markowitz model, allowing it to provide better results than the 1/n rule.

Suggested Citation

  • Ortiz, Roberto & Contreras, Mauricio & Mellado, Cristhian, 2023. "Regression, multicollinearity and Markowitz," Finance Research Letters, Elsevier, vol. 58(PC).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323009224
    DOI: 10.1016/j.frl.2023.104550
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    References listed on IDEAS

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    More about this item

    Keywords

    Markowitz mean–variance optimization G11; Estimation of optimal portfolio weights G11; Financial econometrics C58; Multicollinearity C58;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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