Master the use of Altman Z-Score to identify financially distressed companies and strengthen your investment decisions
The Altman Z-score course offers a comprehensive exploration of one of the most influential and enduring models for predicting corporate bankruptcy and assessing financial strength. Developed by Professor Edward Altman in 1968, the Z-score model remains a cornerstone tool for investors, analysts, and financial professionals worldwide.
What you’ll learn
- Understand the structure, purpose, and components of the Altman Z-Score model.
- Calculate and interpret a company’s Altman Z-Score using real financial data.
- Identify financial distress, bankruptcy risks, and assess corporate financial strength.
- Analyze the five key financial ratios (working capital, retained earnings, EBIT, market equity value, sales) behind the Z-Score.
- Apply the Altman Z-Score to investment decisions, credit risk assessments, and portfolio management.
- Distinguish between healthy, distressed, and at-risk companies using clear Z-Score thresholds.
- Recognize the strengths and limitations of the Altman Z-Score, including its application across different industries and international contexts.
- Use supporting tools like the Beneish M-Score to verify the reliability of financial statements.
- Integrate Altman Z-Score analysis into broader fundamental and financial analysis workflows.
Course Content
- Core course content –> 4 lectures • 1hr 7min.
- Appendix – VingeGPT demo of Altman Z-score & Beneish M-score –> 1 lecture • 3min.
Requirements
The Altman Z-score course offers a comprehensive exploration of one of the most influential and enduring models for predicting corporate bankruptcy and assessing financial strength. Developed by Professor Edward Altman in 1968, the Z-score model remains a cornerstone tool for investors, analysts, and financial professionals worldwide.
Participants will delve into the historical background, rationale, and construction of the Altman Z-score, gaining insight into how and why it continues to dominate failure prediction models even after more than 45 years. The course emphasizes the selection of critical financial ratios, the application of Multiple Discriminant Analysis (MDA), and the establishment of objective statistical weights to predict financial distress with high accuracy.
Through an in-depth breakdown of the five key financial ratios—working capital to total assets, retained earnings to total assets, EBIT to total assets, market value of equity to total liabilities, and sales to total assets—students will learn how each factor contributes to a company’s financial stability. Practical examples and real-world case studies will be used to illustrate interpretation, providing clear guidelines for classifying companies into distress, grey, and safe zones based on Z-score thresholds.
Additionally, the course discusses:
- The relationship between financial statement trustworthiness and supporting tools like the Beneish M-score.
- The evolution of Altman’s work into the Z’-Score and Z”-Score for broader international applicability.
- The limitations of applying these models, particularly for financial companies.
By the end of this course, students will be able to:
- Accurately calculate and interpret Altman Z-scores.
- Use Z-scores to support investment decisions and risk assessments.
- Understand the practical applications and limitations of bankruptcy prediction models in various industries and geographies.
This course is essential for anyone engaged in financial analysis, investment management, or corporate finance who seeks to enhance their toolkit with a proven, statistically sound methodology.