On the Use of Multidimensional Data Analysis Techniques for Corporate Valuation
Georgeta Vintila and
Ştefan Gherghina
Modern Applied Science, 2014, vol. 8, issue 3, 202
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.
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://ccsenet.org/journal/index.php/mas/article/download/35086/20610 (application/pdf)
https://ccsenet.org/journal/index.php/mas/article/view/35086 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ibn:masjnl:v:8:y:2014:i:3:p:202
Access Statistics for this article
More articles in Modern Applied Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().