Variables Important for Bankruptcy Prediction - A Logit Binary Approach
(2013) NEKH01 20122Department of Economics
- Abstract (Swedish)
- The purpose of this bachelor thesis is to estimate our own bankruptcy prediction model using logit binary data. Our choice of variables is based on Altman’s Z-score model 1968. A comparison is then done between results in Altman and our findings. We perform our estimates on 114 listed Nordic companies, where 37 of them went bankrupt during 2002-2012.
We find that our estimated model can categorize defaulting and non-defaulting firms best, two years prior to the event of bankruptcy. This is done with a 76,8 per cent accuracy. Finally, we show that our model can predict bankruptcy of Nordic firms better than Altman’s Z-score model.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/3469994
- author
- Augustsson, Viktor LU and Taurell, Oscar
- supervisor
- organization
- course
- NEKH01 20122
- year
- 2013
- type
- M2 - Bachelor Degree
- subject
- keywords
- bankruptcy prediction, Z-score model, logit binary, maximum likelihood
- language
- English
- id
- 3469994
- date added to LUP
- 2013-02-18 12:52:34
- date last changed
- 2013-02-18 12:52:34
@misc{3469994, abstract = {{The purpose of this bachelor thesis is to estimate our own bankruptcy prediction model using logit binary data. Our choice of variables is based on Altman’s Z-score model 1968. A comparison is then done between results in Altman and our findings. We perform our estimates on 114 listed Nordic companies, where 37 of them went bankrupt during 2002-2012. We find that our estimated model can categorize defaulting and non-defaulting firms best, two years prior to the event of bankruptcy. This is done with a 76,8 per cent accuracy. Finally, we show that our model can predict bankruptcy of Nordic firms better than Altman’s Z-score model.}}, author = {{Augustsson, Viktor and Taurell, Oscar}}, language = {{eng}}, note = {{Student Paper}}, title = {{Variables Important for Bankruptcy Prediction - A Logit Binary Approach}}, year = {{2013}}, }