dc.contributor.advisor |
Jayasooriya SD |
|
dc.contributor.author |
Perera BHD |
|
dc.date.accessioned |
2022 |
|
dc.date.available |
2022 |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Perera, B.H.D. (2022). A Study of corporate financial distress prediction of Sri Lanka : an application of logistic regression analysis and multiple discriminant analysis [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21444 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/21444 |
|
dc.description.abstract |
A financial distressed situation means a company cannot settle its obligations,
liabilities from the operating cash flows or value of total assets is lower than the
aggregate value of the liabilities and equity. The probability of bankruptcy should be
evaluated to reduce its‟ harmful effects. In such a situation, the firms should have to
incur bankruptcy costs. It can be minimized through the evaluation of the possibility
of financial distress. Up to now various types of models are generated to forecast
bankruptcy. In this study, three models are evaluated to compare their distress
predict ion abilit y within the Sri Lankan Context. They are Alt man‟s (1968) and
Springate Model (1978) and Grover Model (2001). Therefore, the objective of this
research is to identify the applicability of these models in forecasting the financial
distress of listed companies in Sri Lanka. Those models are analyzed within the
listed companies of the Colombo Stock Exchange. The relevant financial data is
collected from the audited financial statements during the period of 2013/142017/18.
Descriptive
Statistics and Regression Analysis are used to analyze collected data
with Multivariate Discriminant Analysis (MDA) as the main method of analysis. The
objective of this method is to identify groups of samples from a group of predictors
by finding the relationship of the variables which maximize the deviance among the
populations being studied.
The study findings reveal that Alt man‟s model has a higher accuracy rate in
predicting financial distress in a non-distressed sample rather than a distressed
sample and can predict financial distress before one year to bankruptcy. Yet the
Springate model has an excellent predicting ability both in distressed and nondistressed
samples. And also, it can reveal a symptom of financial distress before
three years to the bankruptcy. Therefore, it can be concluded that the Springate
model is performed well than Alt man‟s model wit hin the Sri Lankan context. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
ALTMAN’S MODEL |
en_US |
dc.subject |
SPRINGATE MODEL |
en_US |
dc.subject |
MDA |
en_US |
dc.subject |
CORPORATE FINANCIAL DISTRESS PREDICTION - Sri Lanka |
en_US |
dc.subject |
FINANCIAL DISTRESS |
en_US |
dc.subject |
FINANCIAL MATHEMATICS - Dissertation |
en_US |
dc.subject |
MATHEMATICS – Dissertation |
en_US |
dc.title |
A Study of corporate financial distress prediction of Sri Lanka : an application of logistic regression analysis and multiple discriminant analysis |
en_US |
dc.type |
Thesis-Abstract |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.degree |
MSc in financial Mathematics |
en_US |
dc.identifier.department |
Department of Mathematics |
en_US |
dc.date.accept |
2022 |
|
dc.identifier.accno |
TH4922 |
en_US |