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Predicting Company Performance By Discriminant Analysis

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  • Dumitra STANCU
  • Andrei-Tudor STANCU

Abstract

This paper aims at evaluating the performance through discriminant analysis of 20 companies traded on the Bucharest Stock Exchange (BVB). As these companies are similar in terms of business profile (manufacturing industry), we choose ten financial indicators that relate to stock value (PRICE, BETA, ALPHA, etc.) and book value (Debt / Equity, ROA and ROE) to assess and classify the companies as good or bad. For a sustainable characterization the average value of the financial indicators is estimated between the first quarter of 2005 and third quarter of 2013. The initial grouping is made according to return on assets (ROA) and splits the sample into 10 “good and 10 “bad companies. We find that discriminant analysis correctly validates the classification of firms by ROA criterion in 90% of cases (18 of 20 companies). Moreover, our analysis establishes that ROA is of first importance in evaluating company performance as suggested by the F test-statistic and Wilks'Lambda coefficient.

Suggested Citation

  • Dumitra STANCU & Andrei-Tudor STANCU, 2014. "Predicting Company Performance By Discriminant Analysis," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 8(1), pages 1173-1180, November.
    • Handle: RePEc:rom:mancon:v:8:y:2014:i:1:p:1173-1180
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