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Evaluation of the financial condition of companies after the announcement of arrangement bankruptcy: application of the classical and Bayesian logistic regression

100%
Pawełek B., Kostrzewska J., Kostrzewski M., Gałuszka K.
Przegląd Statystyczny
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2020
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vol. 67
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issue 1
5-32
EN
The aim of this paper is to present the results of an assessment of the financial condition of companies from the construction industry after the announcement of arrangement bankruptcy, in comparison to the condition of healthy companies. The logistic regression model estimated by means of the maximum likelihood method and the Bayesian approach were used. The first achievement of our study is the assessment of the financial condition of companies from the construction industry after the announcement of bankruptcy. The second achievement is the application of an approach combining the classical and Bayesian logistic regression models to assess the financial condition of companies in the years following the declaration of bankruptcy, and the presentation of the benefits of such a combination. The analysis described in the paper, carried out in most part by means of the ML logistic regression model, was supplemented with information yielded by the application of the Bayesian approach. In particular, the analysis of the shape of the posterior distribution of the repeat bankruptcy probability makes it possible, in some cases, to observe that the financial condition of a company is not clear, despite clear assessments made on the basis of the point estimations.
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GARCH Models of Time Series on DAM

84%
Ganczarek A., University of Economics in Katowice D. o. S.
Acta Universitatis Lodziensis. Folia Oeconomica
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2007
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vol. 206
EN
In this paper an analysis of the time series on the Day Ahead Market (DAM) of the Polish Power Exchange is presented. In this analysis Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are used to describe the time series of rates of return of price of electric energy on DAM. This analysis is based on the data from July 2002 to June 2004.
PL
W pracy została przedstawiona analiza szeregów czasowych stóp zwrotu cen energii elektrycznej notowanych na rynku dnia następnego (RDN) Towarowej Giełdy Energii SA od lipca 2002 do czerwca 2004 r. za pomocą modeli GARCH. Celem pracy jest odpowiedź na pytanie, czy modele GARCH efektywnie opisują kształtowanie się cen energii elektrycznej na parkiecie polskiej giełdy energii i czy można je wykorzystywać do modelowania szeregów czasowych stóp zwrotu cen energii elektrycznej.
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