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dc.contributor.advisorDr. Nguyen Thi Thuy Linhen_US
dc.contributor.authorNguyen Thi Phuong Tramen_US
dc.description.abstractBankrupt prediction is practical research topic and attractsmore attention of debtors, creditors, shareholders and other stakeholders. Moreover, it can be applied in a wide variety of situations to business managers make crucial decision. The bankruptcy prediction models have been developed based on old original modes ofAltman(1968), Ohlson(1980) and Zmijewski(1984)usingmultivariate discriminate, logit and probit analysis respectively. This thesisconducted the comparison of predictive power among these modelsusingVietnameselisted firms during the period from 2008 to 2014. The data is taken from listed companies in HOSE and HNX stock market and characterized the determinants of financial distress in terms of firm accounting andfinancial ratios. To compare the predictive power of these models one year, two years and three year beforehand bankruptcy, the analysis of differences of accuracy rates and Receiver Operating Curves is applied. Overall, Ohlson’sprobit model (1980) performed most accurate on the Vietnam listed companies within investigation periods. This implies that Ohlson’smodel is the best predictor for bankruptcy likelihood for the listed companied in Vietnam. However, since the unstable accuracy rates and the highest frequency of Type I and Type II errors, such resultshould be set into perspective and studied cautiously.en_US
dc.format.medium63 p.en_US
dc.publisherUniversity of Economics Ho Chi Minh City; VNP (Vietnam – The Netherlands Programme for M.A. in Development Economics)en_US
dc.subjectBankruptcy predictionen_US
dc.subjectMultivariate discriminate analysisen_US
dc.subjectLogit modelen_US
dc.subjectProbit modelen_US
dc.titleComparison of accountin-based bankruptcy prediction models of Altman(1968), Ohlson(1980) nad Zmijewski(1984) using Vietnamese listed companies during 2008-2014en_US
dc.typeMaster's Thesesen_US
ueh.specialityDevelopment Economics = Kinh tế phát triểnen_US
item.openairetypeMaster's Theses-
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