Einladung zu zwei Seminarvortr=E4gen von
Prof. Adi Raveh
School of Business Administration and Statistics Department
The Hebrew University of Jerusalem, Israel
THE GREEK BANKING SYSTEM: REANALYSIS OF PERFORMANCE
Abstract:
Multiattribute Evaluation of Greek Banking Performance has been done
recently by Zopounidis et.al. (1995). They used an ordinal regression
analysis as well as an additive utility model to obtain final ranking
of a representative sample of greek banks. In this paper we reanalyze
their data by means of two multivariate analysis methods. One method
is a nonmetric multidimensional saling type called Smalliest Space
Analysis (SSA-I), which is designated to analyze variables (e.g., 7
attributes). The second method is called Co-plot. It is also a
graphic display that is designated to analyze observations (e.g., 16
banks) and attributes simultaneously. Some further comments and
findings are uncovered from our analysis.
key words: Banking Performance, Co-plot, Graphic Display, Smallest
Space Analysis
Zeit: Montag, 6.5.1996, 13.00 Uhr
Ort:
Kleiner Sitzungssaal, =D6sterreichisches Institut f=FCr Wirtschaftsforschu=
ng (WIFO)
Arsenal, Objekt 20
1030 Wien
und
CO-PLOT DISPLAY TECHNIQUE AS AN AID TO THE PREDICTION OF CORPORATE
BANKRUPTCY
Abstarct:
CO-PLOT, a new graphic display method for multivariate data analysis,
is introduced and used to aid the prediction of corporate bankruptcy.
Co-plot maps the rows of a matrix in such a way that similar rows
(observations) will be closely located on the map. The sample units
are exhibited as n points and the variables as p arrows, relative to
the same axis and origin. Co-plot enables the simultaneous study of
observations and variables for a set of data, hence its name. This
method is applied here to study similarity among companies, the
correlation structure among financial ratios (variables), and the
mutual relationships between the companies' observations and
financial ratios. Co-plot yielded clearer findings for the data set
analyzed previously by Altman for the same purpose of prediction.
key words: Dissimilarity, Maximum Correlation, Multidimensional
Scaling (MDS).
Zeit:
Dienstag, 7.5.1996, 16.00 Uhr
Ort:
HS 12, BWZ, Br=FCnner Stra=DFe 72, 1210 Wien
Peter Brandner
Department of Economics email: peter.brandner(a)univie.ac.at
University of Vienna voice: +43-1-40103-3371
Hohenstaufengasse 9 fax: +43-1-5321498
A-1010 Vienna, Austria
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