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Hierarchical PCA and Applications to Portfolio Management

Author

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  • Marco Avellaneda

    (Courant Institute of Mathematical Sciences, NYU)

Abstract

Es ampliamente conocido que los factores de riesgo comunes derivados del PCA más allá de la primera eigenportafolio son generalmente difíciles de interpretar y, por lo tanto, de utilizar en la gestión práctica de la cartera. Exploramos un enfoque alternativo (HPCA) que hace un fuerte uso de la partición del mercado en sectores. Demostramos que este enfoque no conduce a la pérdida de información con respecto al PCA en el caso de la renta variable (constituidos por el S&P 500) y también que los factores comunes asociados admiten interpretaciones simples. El modelo también se puede utilizar en mercados en los que los sectores tienen información asincrónica de precios, como single-name swaps de incumplimiento de crédito, generalizando las obras de Cont y Kan (2011) e Ivanov (2016).

Suggested Citation

  • Marco Avellaneda, 2020. "Hierarchical PCA and Applications to Portfolio Management," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 15(1), pages 1-16, Enero - M.
    • Handle: RePEc:imx:journl:v:15:y:2020:i:1:p:1-16
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    File URL: https://www.remef.org.mx/index.php/remef/article/view/446
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    Citations

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    Cited by:

    1. Chen, Dachuan, 2024. "High frequency principal component analysis based on correlation matrix that is robust to jumps, microstructure noise and asynchronous observation times," Journal of Econometrics, Elsevier, vol. 240(1).
    2. Rama Cont, 2023. "In memoriam: Marco Avellaneda (1955–2022)," Mathematical Finance, Wiley Blackwell, vol. 33(1), pages 3-15, January.
    3. Choi, Jungjun & Yang, Xiye, 2022. "Asymptotic properties of correlation-based principal component analysis," Journal of Econometrics, Elsevier, vol. 229(1), pages 1-18.

    More about this item

    Keywords

    returns; blocks; PCA; HPCA; portfolio;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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