USAGE OF THE MAIN COMPONENTS ANALYSIS IN THE MANAGEMENT OF THE INVESTMENT PORTFOLIO
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Authors:
• Dan ARMEANU, Ph.D.Professor, email: darmeanu@yahoo.com, Afiliation: Academy of Economic Studies Bucharest
• Andreea NEGRU, Ph.D.Student, Afiliation: Academy of Economic Studies BucharestPages:
• 65|74 -
Abstract:
When managing investment portfolios on integrated capital markets, beyond the models put forth by the modern portfolio theory, (the Markowitz model, the CML model, the CAPM model, the Treynor-Black model and more), one can successfully resort to the statistical and mathematical tools made available by the multidimensional data analysis. The reason why we shall use those tools in our analysis is simple: they make it possible to reduce the number of variables in the analysis while preserving much of the information included in the initial data (analysis of the main components); they also outline the extent to which common, latent factors as well as the uncommon factors act upon the respective variables (factorial analysis) and they make it possible to create relevant categories for all observations (shape recognition methods and techniques). In this article we shall deploy informational synthesis instruments (the analysis of main components and factorial analysis) as well as methods and techniques of recognizing shapes (cluster analysis and discriminating analysis) to calculate the financial strength of 20 companies whose shares are describes as ”blue chips” on the German, Polish and Romanian stock markets (being included into the DAX, WIG 20 and BET indexes). Namely, they are: ADIDAS AG, BMW AG, COMMERZBANK AG, DAIMLER AG, LUFTHANSA AG, METRO AG, SIEMENS AG, ASSECO POLAND SA, CEZ GROUP, GLOBAL TRADE CENTER SA, LOTOS GROUP, PKO BANK POLSKI, TVN SA, BRD SA, BANCA TRANSILVANIA SA, ALRO SLATINA SA, PETROM SA, ROMPETROL SA, CNTEE TRANSELECTRICA SA and SNTGN TRANSGAZ SA. When managing the investment portfolios on integrated capital markets, the usage of those methods generate relevant classifications of companies that are listed on the stock market and also make it possible to develop very useful prediction instruments.
