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A Study of corporate financial distress prediction of Sri Lanka : an application of logistic regression analysis and multiple discriminant analysis

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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


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