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Author
Bieszk-Stolorz Beata (Uniwersytet Szczeciński), Markowicz Iwona (Uniwersytet Szczeciński)
Title
Application of Models of Survival Analysis in the Assessment of the Situation of Macrosectors of Listed Companies
Source
Optimum : Economic Studies, 2018, nr 1(91), s. 3-15, rys., tab., bibliogr. s. 14-15
Keyword
Spółki giełdowe, Analiza przeżycia, Rynek kapitałowy
Stock market companies, Survival analysis, Capital market
Note
JEL Classification: C10, C14, C41, G01
summ.
Abstract
Goal - The goal of the article is the assessment of the possibilities of recovery after decrease of prices of shares of companies listed on the Warsaw Stock Exchange in the years 2008-2009 and 20112013 in particular macrosectors: industrials, financials and services. The probability and intensity of increase and decrease of prices were analysed. Research methodology - Selected methods of survival analysis were applied. The Kaplan-Meier estimator was used in the analysis of the probability of increase and decrease of prices of shares in the macrosectors. The intensity of decrease and increase of prices was assessed by means of the empirical hazard model and the proportional Cox model. Threshold values of the increase and decrease of prices were calculated on the basis of changes of the WIG index in analysed periods. Comparative analysis of these two periods was also conducted. Score - The hypothesis about a similar situation of macrosectors during the financial crisis and in the bear market was confirmed. In case of the financials macrosector, its reaction to the market situation was the strongest in both the decrease and increase of share prices. The companies of the industrials macrosector were in better situation than the financial companies. The service companies reacted weakly on the market changes. Originality /value - The application of the survival analysis methods in the study of the capital market. (original abstract)
Accessibility
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
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Bibliography
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  1. Balicki A., 2006, Analiza przeżycia i tablice wymieralności, PWE, Warszawa.
  2. Bieszk-Stolorz B. Markowicz I., 2011, Wykorzystanie modelu proporcjonalnego hazardu Coxa do oceny czasu od spadku cen akcji spółek giełdowych w okresie kryzysu finansowego do ich wzrostu, "Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu" nr 183, Wydawnictwo UE we Wrocławiu, Wrocław, pp. 47-54.
  3. Bieszk-Stolorz B., Markowicz I., 2012, Modele regresji Coxa w analizie bezrobocia, CeDeWu, Warszawa.
  4. Bieszk-Stolorz B., Markowicz I., 2017, The assessment of the situation of listed companies in macrosectors in a  bear market - duration analysis models, [in:] Gardoń A., Kozyra C., Mazurek E. (eds.), "Applications of Mathematics and Statistics in Economics 2017. Conference Proceedings Full Text Papers", 20th International Scientific Conference AMSE, Szklarska Poręba 30th August - 3rd September 2017, Wrocław, pp.17-26. DOI: 10.15611/amse.2017.20.02.
  5. Cox D. R., Oakes D., 1984, Analysis of Survival Data, Chapman and Hall, London.
  6. Deville L., Riva F., 2007, Liquidity and Arbitrage in Options Markets: A Survival Analysis Approach, "Review of Finance", vol. 11, issue 3, pp. 497-525, DOI: 10.1093/ rof/rfm021.
  7. GPW database, http://www.gpw.pl/analizy_i_statystyki, access: 15.06.2016.
  8. Hosmer D. W., Lemeshow S., 2000, Applied Logistic Regression, John Wiley & Sons. Inc., New York.
  9. http://biznes.pl/gielda/profile/swiat/sp-500-us.402.2.6.profile-wykresy- s.html, access: 10.06.2016.
  10. Kaplan E. L., Meier P., 1958, Nonparametric estimation from incomplete observations, "Journal of the American Statistical Association", vol. 53, no. 282, pp. 457-481, DOI: 10.2307/2281868.
  11. Kleinbaum D. G., Klein M., 2005, Survival Analysis. A Sef-Learning Text, SpringerVerlag, New York.
  12. Landmesser J., 2013, Wykorzystanie metod analizy czasu trwania do badania aktywności ekonomicznej ludności w Polsce, Wydawnictwo SGGW, Warszawa.
  13. Lunde A., Timmermann A., 2004, Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets, "Journal of Business & Economic Statistics", vol. 22, no. 3, pp. 253-273, DOI: 10.1198/073500104000000136.
  14. Markovitch D. G., Golder P. N., 2008, Findings - Using Stock Prices to Predict Market Events: Evidence on Sales Takeoff and Long-Term Firm Survival, "Marketing Science", vol. 27, issue 4, pp. 717-729, DOI: 10.1287/mksc.1070.0325.
  15. Markowicz I., Stolorz B., 2009, Model proporcjonalnego hazardu Coxa przy różnych sposobach kodowania zmiennych, "Przegląd Statystyczny", vol. 2, issue 56, pp. 106-115.
  16. Olbryś J., Majewska E., 2015, Bear Market Periods During the 2007-2009 Financial Crisis: Direct Evidence From the Visegrad Countries, "Acta Oeconomica", vol. 65(4), pp. 547-565, DOI: 10.1556/032.65.2015.4.3.
  17. Rocznik Giełdowy 2012, https://static.gpw.pl/pub/files/PDF/rocznik2012/GPW 102_Rocznik2012_Final.pdf. access: 12.06.2016.
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ISSN
1506-7637
Language
eng
URI / DOI
http://dx.doi.org/doi.org/10.15290/oes.2018.01.91.01
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