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Being an outlier: a company non-prosperity sign?

Author

Listed:
  • Lucia Svabova

    (University of Zilina, Slovak Republic)

  • Marek Durica

    (University of Zilina, Slovak Republic)

Abstract

Research background: The state of financial distress or imminent bankruptcy are very difficult situations that the management of every company wants to avoid. For these reasons, prediction of company bankruptcy or financial distress has been recently in a focus of economists and scientists in many countries over the world. Purpose of the article: Various financial indicators, mostly financial ratios, are usually used to predict the financial distress. In order to create a strong prediction model and a statistically significant prediction of bankruptcy, it is advisable to use a deep statistical analysis of the data. In this paper, we analysed the real financial ratios of Slovak companies from the year 2017. In the phase of data preparation for further analysis, we checked the existence of outliers and found that there are some companies that are multivariate outliers because are significantly different from other companies in the database. Thus, we deeply focused on these outlying companies and analysed whether to be an outlier is a sign of financial distress. Methods: We analysed whether there are much more non-prosperous companies in the set of outlier companies and if their financial indicators are significantly different from those of the prosperous companies. For these analyses, we used testing of the statistical hypotheses, such as the test for equality of means and chi-square test. Findings & Value added: The ratio of non-prosperous companies between the outliers is significantly higher than 50 % and the attributes of non-prosperity and being an outlier are dependent. The means of almost all financial ratios of prosperous and non-prosperous companies among outliers are significantly different.

Suggested Citation

  • Lucia Svabova & Marek Durica, 2019. "Being an outlier: a company non-prosperity sign?," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(2), pages 359-375, June.
  • Handle: RePEc:pes:ierequ:v:14:y:2019:i:2:p:359-375
    DOI: 10.24136/eq.2019.017
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    Citations

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    Cited by:

    1. Pavol Durana & Katarina Valaskova & Darina Chlebikova & Vladislav Krastev & Irina Atanasova, 2020. "Heads and Tails of Earnings Management: Quantitative Analysis in Emerging Countries," Risks, MDPI, vol. 8(2), pages 1-20, June.
    2. Rafael Becerra-Vicario & David Alaminos & Eva Aranda & Manuel A. Fernández-Gámez, 2020. "Deep Recurrent Convolutional Neural Network for Bankruptcy Prediction: A Case of the Restaurant Industry," Sustainability, MDPI, vol. 12(12), pages 1-15, June.
    3. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    4. Artur Sajnóg & Anna Rogoziñska-Pawe³czyk, 2022. "Executive compensation and the financial performance of Polish listed companies from the corporate governance perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(2), pages 459-480, June.
    5. Jaroslaw Kaczmarek & Sergio Luis Nanez Alonso & Andrzej Sokolowski & Kamil Fijorek & Sabina Denkowska, 2021. "Financial threat profiles of industrial enterprises in Poland," Oeconomia Copernicana, Institute of Economic Research, vol. 12(2), pages 463-498, June.
    6. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    7. Katarina Valaskova & Pavol Durana & Peter Adamko & Jaroslav Jaros, 2020. "Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities," JRFM, MDPI, vol. 13(5), pages 1-16, May.
    8. Milos Poliak & Lucia Svabova & Jan Benus & Ebru Demirci, 2022. "Driver Response Time and Age Impact on the Reaction Time of Drivers: A Driving Simulator Study among Professional-Truck Drivers," Mathematics, MDPI, vol. 10(9), pages 1-16, April.

    More about this item

    Keywords

    bankruptcy prediction models; financial ratios; failure prediction; financial distress;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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