Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/147412
Title: A REVISIT TO ALTMAN’S Z‐SCORE MODEL
Authors: NG CHI HUNG BRENDON
Issue Date: 2010
Citation: NG CHI HUNG BRENDON (2010). A REVISIT TO ALTMAN’S Z‐SCORE MODEL. ScholarBank@NUS Repository.
Abstract: The recent global economic crisis has witnessed a considerable number of corporate firms turning to bankruptcy proceedings; these firms are not confined to small ones but include many well?established publicly listed companies. This once again highlights the importance of having a reliable model to identify companies that are on the verge of failing. In this study, the fundamental concept underlying Altman’s Z?Score Model is studied using logit regression. The sample includes 94 bankrupt manufacturers and 94 matching non?bankrupt ones that are based in the U.S. over the period 1991?2004. As a comparison, Model 1, while retaining two of Altman’s variables (retained earnings)/(Total Assets) and (Market Value of Equity)/(Book Value of Total Debts) , introduces two new variables (Quick assets)/(Current Assets) and (Net Profit)/(Total Assets)) and these variables suggest that the model, nevertheless, assesses all aspects of a firm’s financial health. Model 1 is based on financial statements one fiscal year prior to bankruptcy, and this four?variable model yields an overall accuracy rate of 77.31%, which is higher than another model with the same four variables, built by multiple discriminant analysis (MDA). Further tests show that Model 2 (based on financial statements three fiscal years prior to bankruptcy) and Model 3 (based on financial statements five fiscal years prior to bankruptcy), which are developed using financial statements three and five fiscal years prior to bankruptcy, produce unpromising prediction results. This leads to the conclusion that logit regression is more superior than MDA and that logit regression has limited ability in long?range prediction.
URI: http://scholarbank.nus.edu.sg/handle/10635/147412
Appears in Collections:Bachelor's Theses

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