Making predictions of the profitability on the financial markets using discriminant analysis

Authors:
Stefan Alexandru Ionescu;Cristiana Stefania Murgoci;Camelia Monica Gheorghe;Emilia Ionescu
Affiliations:
Statistics and Mathematics Department, Romanian American University, Bucharest, Romania;Economics Department, Romanian American University, Bucharest, Romania;Economics Department, Romanian American University, Bucharest, Romania;Economics Department, Academy of Economic Studies, Bucharest, Romania
Venue:
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Year:
2009

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Abstract

In this paper we tried to group in three classes the companies listed without interruption for 6 years from Bucharest Stock Exchange. We used cluster analysis, namely an iterative method of clustering, the k-means algorithm. Using data results, we have made tests for the three classes of prediction using discriminant analysis. Fisher's functions have helped us to make predictions on the affiliation of a new listed company on one of the 3 classes of risk. In this study, emphasis was placed on the liquidity of companies, but also on how efficient are used the raw materials, the basic elements in the current financial crisis. This should give us a clearer picture of companies that are ready to get over this difficult time.