An applied research on the financial ratios as predictors of failure by beaver (1996) in predicting bankruptcy in selected Philippine manufacturing firms

Background: Financial Ratios are one of the simplest instruments often used by firms in gauging their performance. Moreover, via William Beaver's study in the 1960's, it is said that this simple instrument can actually predict the future failure of firms. These ratios, however, vary in pre...

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Bibliographic Details
Main Authors: Ortiz, Cheryl Anne M., San Gabriel, Denise Julienn R., Villanueva, Katrina Anna C.
Format: text
Language:English
Published: Animo Repository 2006
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/6289
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Institution: De La Salle University
Language: English
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Summary:Background: Financial Ratios are one of the simplest instruments often used by firms in gauging their performance. Moreover, via William Beaver's study in the 1960's, it is said that this simple instrument can actually predict the future failure of firms. These ratios, however, vary in predictive power. After testing 30 ratios, Beaver was able to come up with a model consisting of six (6) ratios. A sample of firms in the U.S. was used for Beaver's. An application of the same model in selected manufacturing firms in the Philippines is reported here. Results: Based on the results from the testing performed by the proponents, it was found out that unlike Beaver's findings that the Ratio 1 (Cash Flow to Total Debt Ratio) has the strongest predictive power, Ratio 2 (Net Income to Total Assets Ratio) turns out to have predicted the best and misclassified the least as far as all six (6) ratios are concerned. A comparison of the results per ratio is presented, showing that Ratio 2's average error for the 5-year period is only 34.6% as compared to 50% of Beaver's Ratio. Conclusion: With the results of the test, the proponents of the study found out that the Net Income to Total Assets ratio had the greatest influence in predicting bankruptcy, as it had the lowest percentage of incorrect predictions among the six (6) optimal ratios.