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Equity clusters through the lens of realized semicorrelations

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  • Bollerslev, Tim
  • Patton, Andrew J.
  • Zhang, Haozhe

Abstract

We rely on newly-developed realized semicorrelations constructed from high-frequency returns together with hierarchical clustering and cross-validation techniques to identify groups of individual stocks that share common features. Implementing the new procedures based on intraday data for the S&P 100 constituents spanning 2019-2020, we uncover distinct changes in the “optimal” groupings of the stocks coincident with the onset of the COVID-19 pandemic. Many of the clusters estimated with data post-January 2020 evidence clear differences from conventional industry type classifications. They also differ from the clusters estimated with standard realized correlations, underscoring the advantages of “looking inside” the correlation matrix through the lens of the new realized semicorrelations.

Suggested Citation

  • Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:ecolet:v:211:y:2022:i:c:s016517652100478x
    DOI: 10.1016/j.econlet.2021.110245
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    References listed on IDEAS

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    More about this item

    Keywords

    Clustering; Stock returns; High-frequency data; Semicorrelations; COVID-19;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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