dc.contributor.advisor |
Dai, Jie, 1961- |
|
dc.creator |
Chi, Yuanlong |
|
dc.date.accessioned |
2012-10-23T18:03:38Z |
|
dc.date.available |
2012-10-23T18:03:38Z |
|
dc.date.issued |
2012 |
|
dc.identifier.uri |
http://library2.smu.ca/xmlui/handle/01/24735 |
|
dc.description |
1 online resource (43 leaves) : col. ill. |
|
dc.description |
Includes abstract and appendices. |
|
dc.description |
Includes bibliographical references (leaves 42-43). |
|
dc.description.abstract |
This study uses an adapted factor analysis to recast Altman’s Z-score model and compare the two approaches in terms of their prediction performance. First, a brief review of Altman’s Z-score model and the model of factor analysis method is introduced. Then, some recent breakthroughs of factor analysis are presented to illustrate the theoretical benefits of adapting the method. The data used in this study are described and collected from annual reports of healthy companies and companies who applied Chapter 10K bankruptcies over the time period of 2003 to 2009. Using those data, this study adapts the factor analysis and obtains a new Z-score model. Through comparisons, this study finally evaluates both Altman’s model and the new Z-score model. In conclusion, this study finds that in both aspects of coefficients of determination and predictabilities, the new Z-score model shows better performance than Altman’s model, thus providing an updated and refined tool for bankruptcy prediction. |
en_CA |
dc.description.provenance |
Submitted by Trish Grelot (trish.grelot@smu.ca) on 2012-10-23T18:03:38Z
No. of bitstreams: 1
chi_yuanlong_mrp_2012.pdf: 1121175 bytes, checksum: c18e90db326cc164fd83d5349adfe95b (MD5) |
en |
dc.description.provenance |
Made available in DSpace on 2012-10-23T18:03:38Z (GMT). No. of bitstreams: 1
chi_yuanlong_mrp_2012.pdf: 1121175 bytes, checksum: c18e90db326cc164fd83d5349adfe95b (MD5) |
en |
dc.language.iso |
en |
en_CA |
dc.publisher |
Halifax, N.S. : Saint Mary's University |
|
dc.title |
A comparative study of Altman's Z-score and a factor analysis approaches to bankruptcy predictions |
en_CA |
dc.type |
Text |
en_CA |
thesis.degree.name |
Master of Finance |
|
thesis.degree.level |
Masters |
|
thesis.degree.discipline |
Finance, Information Systems, & Management Science |
|
thesis.degree.grantor |
Saint Mary's University (Halifax, N.S.) |
|