Extracting Common Factors from Liquidity Measures with Principal Component Analysis on the Polish Stock Market

Joanna Olbrys and Elzbieta Majewska ()
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Elzbieta Majewska: University of Bialystok

A chapter in Advances in Longitudinal Data Methods in Applied Economic Research, 2021, pp 109-122 from Springer

Abstract: Abstract According to the literature, the principal component analysis (PCA) can be utilized to extract common features of a set of economic variables. Therefore, the aim of this research is to assess a possibility of using the PCA to extract common components of liquidity across a sample of equities, and from a set of liquidity measures on the Polish stock market. The database contains the group of 86 WSE-listed companies. Seven liquidity proxies, namely percentage relative spread, percentage realized spread, percentage price impact, percentage order ratio, modified version of the Roll estimator, modified turnover and modified Amihud measure, are utilized in the study. The PCA results reveal that common latent factors in liquidity estimates exist on the Polish stock market. Moreover, the robustness analyses confirm the evidence of common sources in liquidity variation within the whole sample period and three subsamples: the pre-crisis, crisis and post-crisis periods. To the best of the authors’ knowledge, all empirical findings reported here are novel and have not been presented in the previous literature.

Keywords: PCA; Liquidity measure; High-frequency data; Daily data; Warsaw stock exchange; C10; C58; G01; G10; G12 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-63970-9_8

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DOI: 10.1007/978-3-030-63970-9_8

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