OPEN Repository

Welcome to OPEN - the Repository of Open Scientific Publications, run by the Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, previously operating as the CeON Repository. The Repository enables Polish researchers from all fields to openly share their articles, books, conference materials, reports, doctoral theses, and other scientific texts.

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22792 archived items

Recent Submissions

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Usefulness of multi-criteria taxonomy in comparative valuation of stocks – the polish experience
(Melandrium, 2015) Welc, Jacek; Sobczak, Elżbieta; Wroclaw University of Economics and Business
One of the most relevant issues in comparative valuation of stocks is a selection of so-called “peers”, i.e. companies which may be considered similar to the one which is valued (where similarity means similar profitability, expected growth and investment risk). When applying comparative valuation techniques analysts usually deem firms from the same industry to be similar and comparable. However, one of the alternative and more objective approaches to selecting comparables is based on a statistical multi-criteria analysis, where those firms are considered comparable which share similar operating and financial features, regardless of their industrial classifications. In our paper we empirically examine the usefulness of taxonomy-based approach in identifying “peers” for comparative valuation, on the basis of data from the Polish stock market for 2003-2013. We found that in our sample “peer-based” stock portfolios were unable to “beat” the portfolios formed on the ground of raw multiples (where no any inter-company differences in fundamentals are taken into consideration).
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Usefulness of multi-criteria taxonomy in corporate bankruptcy prediction – the Polish experience
(Melandrium, 2017) Welc, Jacek; Sobczak, Elżbieta; Wroclaw University of Economics and Business
One of the essential elements of company’s economic and financial evaluation is ratio analysis. It includes computation and interpretation of multiple bankruptcy risk ratios . When applying accounting ratios in a credit risk evaluation analysts typically either compute and interpret several individual ratios (a univariate approach) or apply some pre - estimated parametric multi - variable econometric tools, such as the Altman model or discriminant function . The problem with the first approach is that it does not take into account the inter - relationships between the individual ratios. The latter approach, in turn, calls for statistical models, whose parameters may not be stable in time and in space. In this paper we empirically examine the usefulness of the alternative approach, that is simple taxonomic ranking, in corporate ban kruptcy risk quantification ( on the basis of data from the Polish stock market ) . We found that this simple non - parametric multivariate method outperforms all other tested approaches (including logit model) in discriminating between bankrupt and healthy firms.
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Typology of Polish Nuts2 Regions Regarding the Intensity of Enterprise Innovation Activity
(Melandrium, 2018) Sobczak, Elżbieta; Głuszczuk, Dariusz; Wroclaw University of Economics and Business
The article presents the classification of Polish NUTS 2 regions regarding the intensity of enterprise innovation activity. The research was carried out taking into account the scale of expenditure incurred by enterprises (input indicators) and the achieved results in the form of e.g., income earned for selling innovative products (output indicators). The classes comprising relatively homogenous Polish NUTS 2 regions were identified for the study. The analysis covering the composition and descriptive parameters was performed in relation to the obtained classes. Multidimensional statistical analysis was used for the research purposes, with particular emphasis on cluster analysis methods. The study covered 16 Polish NUTS 2 regions in the years 2008 and 2016. The statistical information, indispensable in identifying and quantifying enterprise innovation activity level in the cross-section of Polish NUTS 2 regions, was collected from the Local Data Bank (LDB), the largest Polish database about innovations. The objective of the study was to assess the diversity and transformations in Polish NUTS 2 regions’ classification regarding input and output indicators of enterprise innovation activity level in the years 2008 and 2016.
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Educational Potential and the Situation of the Youth on the Labour Market in the European Union Regions
(Melandrium, 2018) Bal-Domańska, Beata; Sobczak, Elżbieta; Wroclaw University of Economics and Business
The study is focused on the relationship between educational potential and labor market. Educational potential is defined as the resource of knowledge and skills in the region expressed by the level of formal education, the scientific potential, and the tendency to continue to improve qualifications. The labour market is represented by the young people, who enter the labour market after obtaining formal education. The purpose of the study is to assess the spatial autocorrelation of educational potential and the situation of young people in the cross - section of the NUTS - 2 European Union regions in 2016. The analytical tools were spatial statistics (local and global I Moran). The obtained results indicate strong tendency for cluster development . This was very well visible in case of the long life learning indicator and employment rate of young people neither in education nor training. The lowest tendency for clustering was observed in case of early leavers form education and training. Furthermore the results suggest the significance of education for the development of labour market for young people
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Specialization in smart growth sectors in regional space of the Visegrad Group countries
(Melandrium, 2014) Sobczak, Elżbieta; Prudzienica, Maja; Wroclaw University of Economics and Business
The study discusses problems of regional specialization in smart growth sectors, i.e. separated according to technological advancement among which there are: high-tech, mid-high, midlow and low-tech industries as well as knowledge-intensive services, less knowledgeintensive services and other sectors. The subject of research covers the structure of workforce in these sectors in NUTS 2 regions of the Visegrad Group member countries in the period 2008-2012. The purpose of the study is to identify the intensity of regional specialization, to classify regions in terms of the values of specialization indices and identification of regions characterized by higher workforce share in high and mid-high technology sector and also knowledge-intensive services comparing to EU 28. Regional specialization indices and multivariate data analysis methods, with particular emphasis on cluster analysis method, were applied in empirical studies. The choice of research problem is justified by the relevance of regional specialization in high-tech economic sectors, referred to as smart growth sectors, as the crucial factor of socio-economic development based on knowledge and innovation