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Using the advanced methods of financial analysis to predict the bankruptcy of companies

Abstract
Due to the increase in corporate bankruptcy cases worldwide, the need has increased to find a way to protect companies from bankruptcy by finding a scientific model that enables business owners to predict it before it occurs. Therefore, the interest in predicting bankruptcy has recently become one of the most critical topics in accounting, finance, and finance. This study aims to find the best ways to predict bankruptcy using advanced financial analysis methods. In order to achieve this purpose, the study methodology relied on the use of quantitative analysis methods first, then qualitative analysis methods, and then the combination of quantitative and qualitative methods, in addition to using business evaluation methods, sensitivity analyzing methods, and a credit health panel. The study began by testing the most critical previous predicting models based on the latest financial data from three years before bankruptcy occurred to ensure that it is still influential today. Then the study established a comprehensive model that could use for all kinds of companies and business sectors in one model. The new model proved that it has a high ability to predict up to 72%. Non-quantitative methods are also used to analyze the annual reports and the CEO’s letters to the shareholders. Finally, quantitative, and non-quantitative methods merged into the comprehensive model. Sensitivity analyses proved that the merge increased the model’s predictive efficiency to 89%. This study will increase the ability of companies to protect themselves from bankruptcy by providing them with a modern model for early prediction of bankruptcy before it occurs. In addition, the recommendations resulting from the study will help companies discover weaknesses in their financial structure and fix them before reaching the final stage of bankruptcy.
Degree
Master 2-years
Other description
MSc in Accounting and Financial Management
URI
https://hdl.handle.net/2077/72486
Collections
  • Master theses
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2022-42.pdf (2.182Mb)
Date
2022-06-30
Author
Meslemani, Ahmad Haitham
Peng, Pai
Keywords
Bankruptcy
predict financial analysis
Corporate evaluation
credit risk management
financial ratio
Failure determinants
Series/Report no.
2022:42
Language
eng
Metadata
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