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dc.contributor.authorLagat, Nicole Jerop
dc.date.accessioned2022-02-03T12:51:12Z
dc.date.available2022-02-03T12:51:12Z
dc.date.issued2021
dc.identifier.urihttp://hdl.handle.net/11071/12578
dc.descriptionSubmitted in partial fulfillment of the requirements for the Degree of Bachelor of Science in Financial Economics at Strathmore Universityen_US
dc.description.abstractThe core objective of the study was to test the applicability of the multiple discriminate analysis model in predicting corporate failure of financially distressed companies in different industries in Kenya based on a 3 part criteria. These companies should have been listed in the Nairobi Securities Exchange as listed companies greatly affect investment and the economy as a whole. Second, the companies should have previously experienced financial distress to the point that it was on the verge of failure. Finally, the companies should have sought assistance from the I,<.enyan Government as a final resort before complete failure. Thus the author was able to pick out 4 companies out of the 62 listed. This will assist various stakeholders in the Kenyan financial industry to react to corporate distress signals early enough to avoid financial failure. Descriptive analysis research design was adopted in this study which was carried out on a total of21 companies classified as either distressed or non-distressed to allow for proper discrimination. The period of study was 20 years ranging from 2000-2019. The audited financial accounts of the chosen companies provided secondary financial data. This data was used to extract liquidity, profitability, efficiency, activity and leverage ratios which were then summed up to anive at the Z-Score. Data analysis was conducted through the use of MS Excel where correlation and regression tests were tabulated. The research findings indicate that the MDA model both for manufacturing(l968) and of non-manufacturing(2006) are reliable in predicting financial distress of companies in Kenya as it predicted accurately 71% of non-distressed corporations and 64% of distressed firms. Furthermore, the findings provide evidence that liquidity (WC/T A), profitability (RE/T A), Efficiency(EBIT/TA) and leverage (MVE/TL) ratios had a major influence on financial distress prediction. However, the activity ratio (Sales/TA) did not have much influence. The outcome of this study suggests that stakeholders in a firm can predict failure before it occurs by paying close attention to liquidity, profitability, efficiency and leverage ratios. This will enable them avoid the losses associated with failures by taking appropriate actions in advance.en_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.titleValidity of the multiple discriminate analysis failure prediction model on corporate financial distress: An analysis of the Kenyan marketen_US
dc.typeUndergraduate Projecten_US


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