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dc.contributorDepartment of Managementen_US
dc.creatorNg, Kam-chuen Paul-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/680-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleUsing financial ratios to develop a bankruptcy model for private limited companies in Hong Kongen_US
dcterms.abstractThe use of private company data to generate the bankruptcy classification model presented in this study makes the model applicable to the needs of financial institutions, accounting firms, portfolio managers, and others when they analyze the solvency of private companies. Using a combination of two techniques - Financial Ratio Analysis and Multiple Discriminant Analysis, the model is made of 14 variables measuring four distinct categories of financial structure of a company. The model is rather accurate in distinguishing between bankrupt and healthy companies. It correctly classifies 82% of companies one year prior to bankruptcy and 70% of the companies two years prior to bankruptcy. It is to be mentioned that when tested by the holdout sample, the model demonstrates its satisfactory predictive ability with an accuracy rate of 80%. The model, however, should not be used by itself. Clearly, a bank credit officer's analysis and judgement of total situation related to a private company are the determining factors in making the loan decision. Likewise, the auditor's judgement is the key factor in making the going concern decision as is the judgement of the portfolio manager in making the investment decision.en_US
dcterms.extentv, 183 leaves ; 30 cmen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued1997en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.B.A.en_US
dcterms.LCSHPrivate companies -- China -- Hong Kongen_US
dcterms.LCSHBankruptcy -- China -- Hong Kongen_US
dcterms.LCSHRatio analysisen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/680