On the Use of Multidimensional Data Analysis Techniques for Corporate Valuation


  •  Georgeta Vintila    
  •  Stefan Gherghina    

Abstract

The aim of this research consists in the investigation of a random sample of companies which belong to five European emerging countries, respectively Hungary, Poland, Russia, Slovakia, and Ukraine, from the valuation perspective, by using multidimensional data analysis techniques. Thus, by employing the principal component analysis, after transforming the initial characteristics there resulted two principal components, also considering the restriction of minimizing the loss of information. Subsequently, by the instrumentality of factor analysis, there resulted two factors required to explain the correlations existing between variables. The usefulness of both multidimensional data analysis techniques emerges from the reduction of the significant number of variables in a lesser number of principal components, respectively factors.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1913-1844
  • Issn(Onlne): 1913-1852
  • Started: 2007
  • Frequency: monthly

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(The data was calculated based on Google Scholar Citations)

Google-based Impact Factor (2018): 6.49

h-index (January 2018): 30

i10-index (January 2018): 163

h5-index (January 2018): 19

h5-median(January 2018): 25

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