COMPARATIVE RISK ANALYSIS OF HUNGARIAN AND ROMANIAN TRADE AND SERVICE COMPANIES

by | Jan 14, 2020 | DOI 2018

Tibor Tarnóczi
University of Debrecen, Faculty of Economics and Business, Institute of Accounting and Finance, Debrecen, Hungary 
Edina Kulcsár
Partium Christian University, Faculty of Economics and Social Science, Department of Economics, Oradea, Romania ​
DOI: https://doi.org/10.31410/eraz.2018.252

​​ ​​ ​​

4th International Conference – ERAZ 2018 – KNOWLEDGE BASED SUSTAINABLE ECONOMIC DEVELOPMENT, Sofia- Bulgaria, June 7, 2018, CONFERENCE PROCEEDINGS published by: Association of Economists and Managers of the Balkans, Belgrade, Serbia;  Faculty of Business Studies, Mediterranean University – Podgorica, Montenegro; University of National and World Economy – Sofia, Bulgaria; Faculty of Commercial and Business Studies – Celje, Slovenia; Faculty of Applied Management, Economics and Finance – Belgrade, Serbia, ISBN 978-86-80194-12-7

Abstract

To sustain the tolerable risk level it is essential to map risk factors. According to the previous, the main aim of our research is to find those factors that affect corporate risk if we measure the corporate risk with the degree of operating and financial leverage. To perform our goal, we have chosen some specific financial ratios of trade and service companies in two neighboring counties of Hungary and Romania. In this research, we performed a comparative risk analysis of Hungarian and Romanian enterprises by investigating the relationship between the degree of operating and financial leverage (DOL, DFL) and specific financial ratios. The database used for risk analysis is based on five-year financial statements data of Hungarian and Romanian companies. To analyze the relationship between operational and financial leverage and financial ratios, we used panel regression models. The panel model combines the analysis of cross-sectional and time series data. The calculations of the comparative corporate risk analysis was performed by using the packages of R statistics system. Based on the results of the analysis we can conclude that the quantile panel regression gives better results than the conventional panel model.

Key words

company risk factors, DOL, DFL, financial ratios, quantile panel data model

References

  1. Alastair, L. D. (2009) Mastering Risk Modelling, Prentice Hall, Financial Times, Pearson Education.
  2. Gallati, R. (2003) Risk management and capital adequacy, The McGraw-Hill Companies, Inc., United States of America, p. 8.
  3. Bélyácz, I. (2004) A kockázat változó szerepe az értékszámításban, akadémiai székfoglaló előadás anyaga, https://www.mta.hu/fileadmin/szekfoglalok/000873.pdf, p. 1.
  4. Knight, F. H. (1921) Risk, Uncertainty, and Profit, Boston MA: Hart, Schaffner and Marx; Houghton Mifflin.
  5. Keynes, J. M. (1937) The General Theory of Employment. Quarterly Journal of Economics, Vol. 51, pp. 209-223.
  6. Bélyácz, I. (2011) Kockázat és bizonytalanság a döntésbeli alkalmazhatóság tükrében. Hitelintézeti szemle, Tizedik évfolyam 4 szám, p. 380.
  7. Molak, V. (1997) Fundamentals of risk analysis and risk management. Lewis Publishers (CRC Press, Inc.), New York.
  8. Cullen, A. C., Frey, C.H. (1999) Probabilistic Techniques in Exposure Assessment: A Handbook for Dealing Variability and Uncertainty in Models and Inputs, Plenum Press, New York.
  9. Wilson, R., Shlyakhter, A. (1997) Uncertainty and Variability in Risk Analysis. (in Molak, V. (ed.): Fundamentals of risk analysis and risk management. Chapter I.3) Lewis Publishers (CRC Press, Inc.), New York.
  10. Conklin, D. W. (2002) Analyzing and managing country risks. Ivey Business Journal, 66 (3) (January/February), 36–41 p.
  11. Gabriel, S. C., Baker, C.B. (1980) Concepts of business and financial risk, American Agricultural Economics Association.
  12. Modigliani, F., Miller, M.H. (1958) The Cost of Capital, Corporation Finance, and the Theory of Investment, American Economic Review 48, 1958, pp. 261-297.
  13. Berk, J., DEMarzo, P. (2014) Corporate Finance, Third Edition, The Pearson Series in Finance, p. 489., p. 496.
  14. Ross, S. A., Westerfield, R. W., Jordan, B. D (2013) Fundamentals of Corporate Finance, Standard Edition, McGraw-Hill Irwin, New York, p. 532.
  15. Ehrhardt, M. C., Brigham E. F (2017) Corporate finance: A Focused Approach, Sixth Edition, South-Western College Pub.
  16. Brealey, R. A., Myers, S. C., Allen, F. (2014). Eleventh Global Edition, Mc Graw Hill Education, UK.
  17. Damodaran, A. (2015) Applied Corporate Finance, Fourth Edition, JohnWiley & Sons, Inc., p. 117, p. 119.
  18. Tarnóczi, T., Fenyves, V. (2010) A vállalatértékelés komplex szimulációs modellje, Társadalomtudományi Csoport. Acta Scientiarum Socialium. Universitas Kaposváriensis. Kaposvár. ISSN 1418-7191, 95-107 p.
  19. Illés, I-né (2007) Vállalkozások pénzügyi alapjai. SALDO Pénzügyi Tanácsadó és Informatikai Zrt., Budapest.
  20. Pálinkó, É., Szabó, M. ( 2006) Vállalati pénzügyek, Typotex, Budapest.
  21. Baltagi, B. H. (2005) Econometric Analysis of Panel Data, Third Edition, John Wiley and Sons., England.
  22. Tarnóczi, T., Fenyves, V., Bács, Z., Böcskei, E. (2015) Versenyképesség és gazdasági etika. Vállalati teljesítmény elemzése panel regresszióval, Polgári Szemle, 12.-ik évf., 1-3 sz., 4 p.
  23. Canay, I. A. (2011) A simple approach to quantile regression for panel data, Econometrics Journal, Vol. 14, No. 3, pp. 368–386. https://doi.org/10.1111/j.1368-423X.2011.00349.x
  24. Firpo, S., Fortin, N. M., Lemieux, T. (2009) Unconditional Quantile Regressions. Econometrica, Vol. 77, No. 3, pp. 953-973. https://doi.org/10.3982/ECTA6822

    ​
Tarnóczi_Kulcsár_COMPARATIVE RISK ANALYSIS OF HUNGARIAN AND ROMANIAN TRADE AND SERVICE COMPANIES_pp-252-265Download