Skip to main content

Analysis of Performance of the Warsaw Stock Exchange Companies from Finance Macrosector in Periods of Crisis

  • Conference paper
  • First Online:
Effective Investments on Capital Markets

Abstract

The aim of the article is the assessment of response to a crisis situation for companies belonging to the macrosector of finance in comparison with other sectors on the Warsaw Stock Exchange. The survival analysis methods were applied. The authors analysed the periods of decrease and of the subsequent increase in share prices during the crisis of 2008–2009 and the bear market of 2011. The Kaplan–Meier estimator of the survival function made possible to assess the probability of decrease and of subsequent increase in the share prices. The similarity of the survival curves was investigated using the log-rank test. The Cox regression model was used to determine the intensity of the decrease and increase in share prices. The analysis made possible to assess and compare the performance of the financial sectors against the background of other sectors in both periods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    A new classification of WSE sectors was introduced in 2017. However, due to the research period prior to that date, this article uses the earlier classification of listed companies.

References

  1. Aalen, O., Borgan, O., Gjessing, H.: Survival and Event History Analysis: A Process Point of View. Springer-Verlag, New York (2008)

    Book  Google Scholar 

  2. Abbasian, E., Nemer, A.Y.: Investigating the recession sustainability of main industries in Tehran stock exchange: using Cox regression. Iran. J. Econ. Stud. 5(1), 101–116 (2016). https://doi.org/10.22099/ijes.2017.26659.1354

    Article  Google Scholar 

  3. Andersson, N.: Estimating companies’ survival in financial crisis: using the Cox proportional hazards model. Dissertation. Retrieved from http://uu.diva-portal.org/smash/get/diva2:723216/FULLTEXT01.pdf (2014)

  4. Balan, ChB, Robu, I.-B., Jaba, E.: The statistical assessment of financial distress risk in the case of metallurgical companies. Metalurgija 54(3), 575–578 (2015)

    Google Scholar 

  5. Bieszk-Stolorz, B.: Analiza historii zdarzeń w badaniu bezrobocia. volumina.pl Daniel Krzanowski, Szczecin (2013)

    Google Scholar 

  6. Bieszk-Stolorz, B., Markowicz, I.: Modele regresji Coxa w analizie bezrobocia. CeDeWu, Warszawa (2012)

    Google Scholar 

  7. Bieszk-Stolorz B, Markowicz, I.: Analiza tendencji zmian cen akcji spółek na Giełdzie Papierów Wartościowych w Warszawie po bessie w 2011 roku. Finanse, rynki finansowe, ubezpieczenia 2(86):375–388. https://doi.org/10.18276/frfu.2017.86-31 (2017)

    Article  Google Scholar 

  8. Bieszk-Stolorz B, Markowicz I.: The assessment of the situation of listed companies in macrosectors in a bear market—duration analysis models. In: Conference proceedings full text papers. Applications of Mathematics and Statistics in Economics, pp. 17–25 (2017). http://amse.ue.wroc.pl/proceedings2017.html. https://doi.org/10.15611/amse.2017.20.02

  9. Cox, D.R., Oakes, D.: Analysis of Survival Data. Chapman and Hall, London (1984)

    Google Scholar 

  10. Deville, L., Riva, F.: Liquidity and arbitrage in options markets: a survival analysis approach. Rev. Finan. 11(3), 497–525 (2007). https://doi.org/10.1093/rof/rfm021

    Article  Google Scholar 

  11. European Commission: Economic crisis in Europe: causes, consequences and responses. European economy, 7/2009 (2009)

    Google Scholar 

  12. Evrensel, A.Y.: Banking crisis and financial structure: a survival-time analysis. Int. Rev. Econ. Finan. 17(4), 589–602 (2008). https://doi.org/10.1016/j.iref.2007.07.002

    Article  Google Scholar 

  13. Gepp, A., Kumar, K.: Predicting financial distress: a comparison of survival analysis and decision tree techniques. Proc. Comput. Sci. 54, 396–404 (2015). https://doi.org/10.1016/j.procs.2015.06.046

    Article  Google Scholar 

  14. GPW database. http://www.gpw.pl/analizy_i_statystyki. Accessed 15 June 2018

  15. Hosmer, D.W., Lemeshow, S.: Applied Logistic Regression, 2nd edn. Wiley, New York (2005). https://doi.org/10.1002/0471722146

    Book  Google Scholar 

  16. https://www.bankier.pl. Accessed 15 June 2018

  17. http://bossa.pl/notowania/pliki/eod/omega/. Accessed 10 June 2018

  18. Kaplan, E.L., Meier, P.: Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53(282), 457–481 (1958). https://doi.org/10.2307/2281868

    Article  Google Scholar 

  19. Kleinbaum,D., Klein, M.: Survival Analysis. A Self-Learning Text, 3rd edn. Springer, New York (2012). https://doi.org/10.1007/978-1-4419-6646-9

    Book  Google Scholar 

  20. Konopczak, M., Sieradzki, R., Wiernicki, M.: Kryzys na światowych rynkach finansowych—wpływ na rynek finansowy w Polsce oraz implikacje dla sektora realnego. Bank i Kredyt 41(6), 45–70 (2010)

    Google Scholar 

  21. Landmesser, J.: Wykorzystanie metod analizy czasu trwania do badania aktywności ekonomicznej ludności w Polsce. Wydawnictwo SGGW, Warszawa (2003)

    Google Scholar 

  22. Markowicz, I.: Statystyczna analiza żywotności firm. Rozprawy i Studia t. (CMIX) 835, Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin (2012)

    Google Scholar 

  23. Markowicz, I., Stolorz, B.: Model proporcjonalnego hazardu Coxa przy różnych sposobach kodowania zmiennych. Przegląd Statystyczny 2(56), 106–115 (2009)

    Google Scholar 

  24. Markovitch, D.G., Golder, P.N.: Findings—using stock prices to predict market events: evidence on sales takeoff and long-term firm survival. Mark. Sci. 27(4), 717–729 (2008). https://doi.org/10.1287/mksc.1070.0325

    Article  Google Scholar 

  25. Matuszyk, A.: Zastosowanie analizy przetrwania w ocenie ryzyka kredytowego klientów indywidualnych. CeDeWu, Warszawa (2015)

    Google Scholar 

  26. Minsky, H.: Stabilizing an Unstable Economy. Yale University Press, London (1986)

    Google Scholar 

  27. NBP Raport: Polska wobec światowego kryzysu gospodarczego. http://www.nbp.pl/aktualnosci/wiadomosci_2009/polska_wobec_swiatowego_kryzysu_gospodarczego_2009.pdf (2009)

  28. Olbryś, J., Majewska, E.: Bear market periods during the 2007–2009 financial crisis: direct evidence from the Visegrad countries. Acta Oeconomica 65(4), 547–565 (2015). https://doi.org/10.1556/032.65.2015.4.3

    Article  Google Scholar 

  29. Pereira, J.: Survival analysis employed in predicting corporate failure: a forecasting model proposal. Int. Bus. Res. 7(5), 9–20 (2014). https://doi.org/10.5539/ibr.v7n5p9

    Article  Google Scholar 

  30. Roszkowska, P., Prorokowski, Ł.: Model of Financial Crisis contagion: a survey-based simulation by means of the modified Kaplan-Meier survival plots. Folia Oeconomica Stetinensia 13(21)/1, 22–55 (2013). https://doi.org/10.2478/foli-2013-0006

    Article  Google Scholar 

  31. Sączewska-Piotrowska, A.: Dynamika ubóstwa w miejskich i wiejskich gospodarstwach domowych. Wiadomości Statystyczne 7, 29–46 (2016)

    Google Scholar 

  32. Tarczyński, W., Tarczyńska-Łuniewska, M., Tarczyński, P.: Scoringowa metoda wyznaczania sektorowego wskaźnika siły fundamentalnej na przykładzie spółek notowanych na Giełdzie Papierów Wartościowych w Warszawie. Rynek Kapitałowy. Skuteczne Inwestowanie, Finanse, rynki finansowe, ubezpieczenia 2(86), 21–31 (2017). https://doi.org/10.18276/frfu.2017.86-02

    Article  Google Scholar 

  33. Wycinka, E.: Modelowanie czasu do zaprzestania spłat rat kredytu lub wcześniejszej spłaty kredytu jako zdarzeń konkurujących. Problemy Zarządzania 13, 3(55)/2, 146–157 (2015). https://doi.org/10.7172/1644-9584.55.10

    Article  Google Scholar 

  34. Yamaguchi, K.: Event History Analysis. SAGE Publications, Newbury Park CA (1991)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Beata Bieszk-Stolorz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bieszk-Stolorz, B., Markowicz, I. (2019). Analysis of Performance of the Warsaw Stock Exchange Companies from Finance Macrosector in Periods of Crisis. In: Tarczyński, W., Nermend, K. (eds) Effective Investments on Capital Markets. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-21274-2_1

Download citation

Publish with us

Policies and ethics