FINANCIAL STRENGTH ANALYSIS OF COMPANIES FINANCED FROM CAPITAL MARKET

Article aims to highlight the financial strength enterprises on the capital market in Romania using this technique for the analysis of principal components. Principal components analysis (PCA) is a multivariate data analysis technique whose main purpose is to reduce the dimension of the observations and thus simplify the analysis and interpretation of data, as well as facilitate the construction of predictive models. A rigorous definition of PCA has been given by Bishop (1995) and it states that PC4 is a linear dimensionality reduction technique, which identifies orthogonal directions of maximum variance in the original data, and projects the data into a lower-dimensionality space formed of a sub-set of the highest-variance components. PC4 is commonly used in economic research, as well as in other fields of activity. When faced with the complexity of economic and financial processes, researchers have to analyze a large number of variables (or indicators), fact which often proves to be troublesome because it is difficult to collect such a large amount of data and perform calculations on it. In addition, there is a good chance that the initial data is powerfully correlated; therefore, the signification of variables is seriously diminished and it is virtually impossible to establish causal relationships between variables. Researchers thus require a simple, yet powerful analytical tool to solve these problems and perform a coherent and conclusive analysis. This tool is PC4..