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Principal Components And Canonical Correlation Analyses As Complementary Tools. Application To The Processing Of Financial Information

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  • Ana GARCÍA-GALLEGO
  • María-Jesús MURES-QUINTANA

    (Universidad de León, Spain)

Abstract

The processing of huge amounts of data (big data) whose generation has been fostered by advances in the information and communications technologies involves a high cost of timing and resources, which can be simplified by the application of data reduction statistical methods, such as Principal Components Analysis (PCA). In this paper a PCA is applied in order to prove its usefulness in reducing financial information expressed as ratios. The achieved results, in terms of variable selection, are next justified by the application of a Canonical Correlation Analysis (CCA). The use of both methods shows they are complementary, since the ratios correlated to the extracted factors in PCA are also important in defining the canonical variates in CCA, showing the relationship between them.

Suggested Citation

  • Ana GARCÍA-GALLEGO & María-Jesús MURES-QUINTANA, 2016. "Principal Components And Canonical Correlation Analyses As Complementary Tools. Application To The Processing Of Financial Information," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 249-266.
    • Handle: RePEc:cys:ecocyb:v:50:y:2016:i:4:p:249-266
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    References listed on IDEAS

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    Cited by:

    1. María Escribano-Navas & German Gemar, 2021. "Gender and Bankruptcy: A Hotel Survival Econometric Analysis," Sustainability, MDPI, vol. 13(12), pages 1-13, June.

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    More about this item

    Keywords

    principal components analysis; canonical correlation analysis; financial information; ratios; big data.;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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