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THE COMPARATIVE RISK ANALYSIS OF SMALL AND MEDIUM ENTERPRISES
Analele Universităţii din Oradea. Ştiinţe economice, 2017-07, Vol.28 (1), p.413-423
[Peer Reviewed Journal]
ISSN: 1222-569X ;EISSN: 1582-5450
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Title:
THE COMPARATIVE RISK ANALYSIS OF SMALL AND MEDIUM ENTERPRISES
Author:
Edina Kulcsar
Subjects:
risk, degree of operating leverage, degree of financial leverage, risk analysis
;
standard deviation, semi-deviation, mean absolute deviation
Is Part Of:
Analele Universităţii din Oradea. Ştiinţe economice, 2017-07, Vol.28 (1), p.413-423
Description:
This paper is dealing with the comparative analysis of corporate risk by applying of different risk quantifying methods used both in national and international literature. The investigation is based on selected number of anonymous small and medium sized enterprises’ simplified financial annual report. In Romania, as in other Central European countries, the small and medium-sized enterprises play an important role on aspect of GDP stimulation and jobs creation. For this research, the data will be ensured by simplified financial reports of 173 small and medium-sized enterprises registered in County Bihor between 2011 and 2012. The selected enterprises are 135 trading firms (78,03%) and 38 manufacturing firms (21,97%). For the corporate risk quantification, firstly, I will use the dynamic risk measures: degree of operating leverage (DOL), degree of financial leverage (DFL) and the product of them degree of combined leverage (DCL). The first two risk ratios will be used further as main features in investigated enterprises grouping. The grouping of investigated enterprises will be carried out by using of K-means non-hierarchical cluster analysis. In the second part of research, I will also calculate the main dispersion measures of Return on Assets (ROA) for each clusters. So, I will carried out the quantification of corporate risk by the following dispersion indicators: standard deviation, semi-deviation, (semi-standard deviation), mean absolute deviation and median absolute deviation. For the better illustration of differences and similarities between each clusters, I will apply metric multidimensional scaling (MDS). The calculations will be carried out in R statistics software program by using kmeans and cmdscale functions. The results of analysis are different in case of investigated methods. According to cluster analysis, the major problem of enterprises is the operating risk, because the value of degree of operating leverage (DOL) shows extremely high (cluster 3.) and low (cluster 1.) values. In term of financial risk, we can conclude that enterprises are well situated, because the values of degree of financial leverage (DFL) are relatively low, only the firms from cluster 1. and cluster 3. should be careful in term of debt level. While the cluster analysis by dynamic risk indicators considers the firms from cluster 1., cluster 3., and cluster 11 as the most risky, the investigated dispersion measures class firms differently. According to this, the firms from cluster 1., and cluster 6. represent an average position and can be considered appropriate in term of risk. The enterprises from cluster 3. and cluster 11. are quite different on aspect of risk, because their points of MDS graphical representation are so far situated.
Publisher:
University of Oradea
Language:
German
Identifier:
ISSN: 1222-569X
EISSN: 1582-5450
Source:
DOAJ Directory of Open Access Journals
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