Credit Analysis: Altman Z-Score

Altman Z-Score: Predicting Financial Distress and Bankruptcy

Introduction

The Altman Z-Score is a widely used financial model that helps predict the likelihood of financial distress and bankruptcy for companies. This model, originally developed for manufacturing firms, employs a combination of financial ratios to calculate a single numerical score. A Z-Score below a certain threshold indicates a higher probability of bankruptcy. This section explores the concept of the Altman Z-Score, its calculation, interpretation, and significance in predicting financial distress and bankruptcy.

Understanding the Altman Z-Score

The Altman Z-Score is a formula that combines multiple financial ratios to evaluate a company's financial health and potential for bankruptcy. The model assigns weights to each ratio based on its relative importance in predicting financial distress. The resulting Z-Score provides an indication of the company's risk of bankruptcy.

Z = 1.2(X1) + 1.4(X2) + 3.3(X3) + 0.6(X4) + 1.0(X5)

Components of the Altman Z-Score

The Altman Z-Score incorporates five financial ratios, denoted as X1, X2, X3, X4, and X5. These ratios represent different aspects of a company's financial condition and are calculated as follows:

X1 = (Current Assets - Current Liabilities) / Total Assets

X2 = Retained Earnings / Total Assets

X3 = EBIT / Total Assets

X4 = Market Value of Stock / Book Value of Liabilities

X5 = Sales / Total Assets

Interpretation of the Altman Z-Score

The Altman Z-Score provides a single numerical value that helps predict the likelihood of financial distress and bankruptcy. A Z-Score below a specified threshold (e.g., 1.81 for manufacturing firms) indicates a higher probability of bankruptcy. The lower the Z-Score, the greater the financial distress and risk of default.

Significance of the Altman Z-Score

The Altman Z-Score is a powerful tool for assessing a company's financial stability and the potential for bankruptcy. By analyzing the Z-Score, investors, creditors, and analysts can gain insights into the company's financial health, risk profile, and likelihood of default. It serves as an early warning system, helping stakeholders identify companies at higher risk and make informed decisions regarding investments, lending, and business relationships.

Example

Let's consider the following financial data for Company XYZ:

Current Assets: $500,000

Current Liabilities: $300,000

Retained Earnings: $200,000

Total Assets: $1,000,000

EBIT: $150,000

Market Value of Stock: $400,000

Book Value of Liabilities: $350,000

Sales: $800,000

X1 = ($500,000 - $300,000) / $1,000,000 = 0.2

X2 = $200,000 / $1,000,000 = 0.2

X3 = $150,000 / $1,000,000 = 0.15

X4 = $400,000 / $350,000 = 1.14

X5 = $800,000 / $1,000,000 = 0.8

Z = 1.2(0.2) + 1.4(0.2) + 3.3(0.15) + 0.6(1.14) + 1.0(0.8) = 1.536

In this example, Company XYZ has an Altman Z-Score of 1.536. As the Z-Score is below the threshold of 1.81 for manufacturing firms, it suggests a higher probability of financial distress or bankruptcy.

Conclusion

The Altman Z-Score is a valuable model for predicting financial distress and bankruptcy. By combining multiple financial ratios, the Z-Score provides a single numerical value that indicates a company's risk of default. A Z-Score below the specified threshold suggests a higher probability of financial distress. By analyzing the Altman Z-Score, stakeholders can assess a company's financial health, identify potential risks, and make informed decisions regarding investments, lending, and business partnerships.

This article takes inspiration from a lesson found in FIN 689 at Pace University.