• Media type: E-Book
  • Title: Multivariate Statistical Analysis Framework as a Tool for Bank Performance Assessment
  • Contributor: Dziechciarz, Jozef Zbigniew [Author]; Strahl, Danuta [Other]
  • Published: [S.l.]: SSRN, [2014]
  • Extent: 1 Online-Ressource (2 p)
  • Language: English
  • Origination:
  • Footnote: In: Herausforderungen der Information Gesellschaft an Datenanalyse und Wissen Verarbeitung
    In: Abstracts
    In: [1998] Technische Universität Dresden
    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 4, 1998 erstellt
  • Description: Multivariate statistical analysis uses techniques of variables selection and aggregation. Numerous economic phenomena belong to the application field of multivariate analysis. Generally all phenomena described by large number of variables may be analyzed within this framework. On the other side, this large number of descriptive variables yields serious problems in assessing and interpreting the message which is carried by those variables values. Assessment of the bank performance is one of the most important fields where multivariate statistical analysis techniques should be applied. Banks are assessed both from outside -- customers, publics, shareholders, investors; and from inside -- bank management. There is continuous need for new, better tools for such an assessment. One of the most interesting suggestions on this field is techniques of multiple criteria decision making framework. The idea exploits the methodology of reference objective approach. This methodology have French equivalent: "but de reference", and German: "Referenzziel". Generally in this methodology the reference point is defined and gives the comparison base for the performance assessment. On the other hand gives the possibility for formulating of the tailored (by the assessing institution) system of measures and standards which may be important in this particular inquiry. The bank assessment process is being done in three steps: Step I - clustering of the measures values for the banks (or branches)Step II - normalizing the measures valuesStep III - construction of the aggregate measure. The performance indicators are classified into three types: Stimuli -- where higher value means better performance; Destimuli -- where low values indicate better performance; and Nominants -- where the best value (or best value interval) is implied -- if the measure has implied value or value within implied interval -- bank performance is positively assessed. Such a general measures classification needs further analysis. In the paper deep inquiry into bank performance measures typology is presented
  • Access State: Open Access