Camelia Catalina Joldes
Bucharest University of Economic Studies, 6 Piata Romana, 1st district, Bucharest, 010374 Romania
2nd International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2018 – Graz, Austria, November 8, 2018, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade, Serbia; ISBN 978-86-80194-13-4
The purpose of this paper is to show how principal component analysis (PCA) can be used to construct the most efficient portfolios. Due to the large number of existing variables, it is difficult to perform statistical analysis of data, but PCA will help us in choosing the best performing shares. Through the PCA we will show the utility of this statistical method in the selection phase of the data. For this study we decided to select a number of representative companies for four central European countries: Czech Republic, Poland, Germany and Austria. The main objective of this analysis is to identify the most important factors indicating the most profitable shares, so we have considered a number of five financial indicators, representative for the selected firms.
Stock selection, principal component analysis, diversification, data reduction, variance
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