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Statistical approach to prediction of financial distress Of listed firms in the Nairobi Securties exchange

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dc.contributor.author NDIEGE, Jack
dc.date.accessioned 2019-01-25T07:32:25Z
dc.date.available 2019-01-25T07:32:25Z
dc.date.issued 2017
dc.identifier.uri https://repository.maseno.ac.ke/handle/123456789/1178
dc.description Masters' Thesis en_US
dc.description.abstract This research project examined the phenomenon of bankruptcy prediction from a developing economy perspective using the Altman Z-score models. These models rank among the bankruptcy models, whose main purpose is to detect the impending bankruptcy in good time. Drawing an empirical data from audited financial statements of firms listed in Nairobi Security Exchange in Kenya, the author tested Altman original Z-score (1968)and the Emerging Markets (1993) models using the dataset of the years ending between 2010 and 2015. Since the most frequently used tool so as to predict financial distress and bankruptcy is through financial analysis of financial ratios, this study employed the same ratios and therefore aimed to make an important contribution to the global discourse on corporate failure prediction in an increasingly globalised world. en_US
dc.language.iso en_US en_US
dc.publisher Maseno University en_US
dc.subject Bankruptcy en_US
dc.title Statistical approach to prediction of financial distress Of listed firms in the Nairobi Securties exchange en_US
dc.type Thesis en_US


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