Altman Z-Score Calculator - Predict Bankruptcy Risk Free

Altman Z-Score Calculator: Predict Bankruptcy Risk

What Is the Altman Z-Score?

The Altman Z-Score is a powerful financial formula that predicts the likelihood of a company going bankrupt within two years. Developed by Professor Edward I. Altman in 1968, this bankruptcy prediction model combines five key financial ratios to assess corporate financial health and credit risk. Investors, creditors, and financial analysts use the Altman Z-Score calculator to evaluate whether a company is in the safe zone, grey zone, or distress zone for potential insolvency.

Altman Z-Score Formula

The Altman Z-Score formula combines five weighted financial ratios to calculate bankruptcy risk:

Z = 1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 1.0X_5

Where:

$X_1 = \frac{\text{Working Capital}}{\text{Total Assets}}$
$X_2 = \frac{\text{Retained Earnings}}{\text{Total Assets}}$
$X_3 = \frac{\text{Earnings Before Interest and Taxes (EBIT)}}{\text{Total Assets}}$
$X_4 = \frac{\text{Market Value of Equity}}{\text{Total Liabilities}}$
$X_5 = \frac{\text{Sales}}{\text{Total Assets}}$

Explanation of Variables

Working Capital (WC): Current Assets minus Current Liabilities. Indicates short-term financial liquidity.
Retained Earnings (RE): Cumulative profits reinvested in the company. Reflects long-term profitability.
EBIT: Earnings before interest and taxes. Measures operating efficiency.
Market Value of Equity (MVE): Number of outstanding shares multiplied by the current share price. Represents shareholder confidence.
Total Liabilities (TL): Sum of current and long-term liabilities.
Sales: Total revenue from goods or services sold.
Total Assets (TA): Sum of current and non-current assets.

How to Calculate Altman Z-Score: Step-by-Step Guide

Calculate Financial Ratios:
- $X_1 = \frac{\text{WC}}{\text{TA}}$
- $X_2 = \frac{\text{RE}}{\text{TA}}$
- $X_3 = \frac{\text{EBIT}}{\text{TA}}$
- $X_4 = \frac{\text{MVE}}{\text{TL}}$
- $X_5 = \frac{\text{Sales}}{\text{TA}}$
Apply Weights to Each Ratio:
- Multiply each $X$ ratio by its corresponding coefficient.
Sum the Weighted Ratios:
- $Z = 1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 1.0X_5$

Numerical Example

Suppose a company has the following financial data (in USD millions):

Working Capital (WC): $50 million
Retained Earnings (RE): $200 million
EBIT: $100 million
Market Value of Equity (MVE): $500 million
Total Liabilities (TL): $400 million
Sales: $600 million
Total Assets (TA): $800 million

Calculating the Ratios:

$X_1 = \frac{50}{800} = 0.0625$
$X_2 = \frac{200}{800} = 0.25$
$X_3 = \frac{100}{800} = 0.125$
$X_4 = \frac{500}{400} = 1.25$
$X_5 = \frac{600}{800} = 0.75$

Calculating the Z-Score:

\begin{align*} Z &= 1.2(0.0625) + 1.4(0.25) + 3.3(0.125) + 0.6(1.25) + 1.0(0.75) \\ &= 0.075 + 0.35 + 0.4125 + 0.75 + 0.75 \\ &= 2.3375 \end{align*}

Interpreting Your Altman Z-Score Results

The Altman Z-Score interpretation follows three risk zones:

Z-Score > 2.99: Safe Zone – Low probability of bankruptcy within two years
1.81 < Z-Score < 2.99: Grey Zone – Uncertain risk; caution advised
Z-Score < 1.81: Distress Zone – High probability of bankruptcy within two years

Result: A Z-Score of 2.34 places the company in the Grey Zone, indicating potential financial instability and elevated credit risk.

Edge Cases and Limitations

Negative Values: Negative inputs for net income, retained earnings, or working capital can significantly lower the Z-Score.
Applicability: The original model is best suited for publicly traded manufacturing companies.
Industry Differences: Non-manufacturing, private, and emerging market companies may require adjusted models (e.g., Z'-Score, Z''-Score).
Economic Conditions: Macro-economic factors are not considered in the model.

Real-World Applications of the Altman Z-Score

When to Use the Altman Z-Score Calculator

Bankruptcy Risk Assessment: Identify early warning signs of financial distress before company failure
Credit Risk Analysis: Help lenders and banks evaluate loan application risks and set appropriate terms
Investment Due Diligence: Guide investors toward financially stable companies and avoid distressed stocks
Corporate Financial Planning: Enable management to monitor financial health and implement corrective strategies
Portfolio Risk Management: Screen investments for bankruptcy risk across multiple holdings

Alternatives

Z'-Score and Z''-Score Models

Z'-Score: Adapted for private manufacturing companies.
Z''-Score: Further adjusted for non-manufacturing and emerging market companies.

Other Models

Ohlson O-Score: A logistic regression model predicting bankruptcy risk.
Zmijewski Score: A probit model alternative focusing on financial distress.

When to Use Alternatives:

For companies outside the manufacturing sector.
When assessing private or non-publicly traded companies.
In different economic contexts or geographical regions.

History

Edward Altman introduced the Z-Score model in 1968 amidst increasing corporate bankruptcies. Utilizing multiple discriminant analysis (MDA), Altman analyzed 66 companies to identify key financial ratios predictive of bankruptcy. The model has since been refined and remains a foundational tool in credit risk assessment.

Additional Considerations

Impact of Financial Manipulation

Companies may engage in accounting practices that temporarily inflate financial ratios.
It's crucial to consider qualitative factors alongside quantitative scores.

Integration with Other Metrics

Combine the Z-Score with other analyses (e.g., cash flow analysis, market trends).
Use as part of a comprehensive due diligence process.

Code Examples

Excel

1' Excel VBA Function for Altman Z-Score Calculation
2Function AltmanZScore(wc As Double, re As Double, ebit As Double, mve As Double, tl As Double, sales As Double, ta As Double) As Double
3    Dim X1 As Double, X2 As Double, X3 As Double, X4 As Double, X5 As Double
4    
5    X1 = wc / ta
6    X2 = re / ta
7    X3 = ebit / ta
8    X4 = mve / tl
9    X5 = sales / ta
10    
11    AltmanZScore = 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5
12End Function
13
14' Usage in a cell:
15' =AltmanZScore(A1, B1, C1, D1, E1, F1, G1)
16' Where A1 to G1 contain the respective input values
17

Python

1## Altman Z-Score Calculation in Python
2def calculate_z_score(wc, re, ebit, mve, tl, sales, ta):
3    X1 = wc / ta
4    X2 = re / ta
5    X3 = ebit / ta
6    X4 = mve / tl
7    X5 = sales / ta
8    z_score = 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5
9    return z_score
10
11## Example usage:
12wc = 50
13re = 200
14ebit = 100
15mve = 500
16tl = 400
17sales = 600
18ta = 800
19
20z = calculate_z_score(wc, re, ebit, mve, tl, sales, ta)
21print(f"Altman Z-Score: {z:.2f}")
22

JavaScript

1// JavaScript Altman Z-Score Calculation
2function calculateZScore(wc, re, ebit, mve, tl, sales, ta) {
3  const X1 = wc / ta;
4  const X2 = re / ta;
5  const X3 = ebit / ta;
6  const X4 = mve / tl;
7  const X5 = sales / ta;
8  const zScore = 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5;
9  return zScore;
10}
11
12// Example usage:
13const zScore = calculateZScore(50, 200, 100, 500, 400, 600, 800);
14console.log(`Altman Z-Score: ${zScore.toFixed(2)}`);
15

Java

1// Java Altman Z-Score Calculation
2public class AltmanZScore {
3    public static double calculateZScore(double wc, double re, double ebit, double mve, double tl, double sales, double ta) {
4        double X1 = wc / ta;
5        double X2 = re / ta;
6        double X3 = ebit / ta;
7        double X4 = mve / tl;
8        double X5 = sales / ta;
9        return 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5;
10    }
11
12    public static void main(String[] args) {
13        double zScore = calculateZScore(50, 200, 100, 500, 400, 600, 800);
14        System.out.printf("Altman Z-Score: %.2f%n", zScore);
15    }
16}
17

R

1## R Altman Z-Score Calculation
2calculate_z_score <- function(wc, re, ebit, mve, tl, sales, ta) {
3  X1 <- wc / ta
4  X2 <- re / ta
5  X3 <- ebit / ta
6  X4 <- mve / tl
7  X5 <- sales / ta
8  z_score <- 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5
9  return(z_score)
10}
11
12## Example usage:
13z_score <- calculate_z_score(50, 200, 100, 500, 400, 600, 800)
14cat("Altman Z-Score:", round(z_score, 2))
15

MATLAB

1% MATLAB Altman Z-Score Calculation
2function z_score = calculate_z_score(wc, re, ebit, mve, tl, sales, ta)
3    X1 = wc / ta;
4    X2 = re / ta;
5    X3 = ebit / ta;
6    X4 = mve / tl;
7    X5 = sales / ta;
8    z_score = 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5;
9end
10
11% Example usage:
12z_score = calculate_z_score(50, 200, 100, 500, 400, 600, 800);
13fprintf('Altman Z-Score: %.2f\n', z_score);
14

C++

1// C++ Altman Z-Score Calculation
2#include <iostream>
3
4double calculateZScore(double wc, double re, double ebit, double mve, double tl, double sales, double ta) {
5    double X1 = wc / ta;
6    double X2 = re / ta;
7    double X3 = ebit / ta;
8    double X4 = mve / tl;
9    double X5 = sales / ta;
10    return 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5;
11}
12
13int main() {
14    double zScore = calculateZScore(50, 200, 100, 500, 400, 600, 800);
15    std::cout << "Altman Z-Score: " << zScore << std::endl;
16    return 0;
17}
18

C#

1// C# Altman Z-Score Calculation
2using System;
3
4class Program
5{
6    static double CalculateZScore(double wc, double re, double ebit, double mve, double tl, double sales, double ta)
7    {
8        double X1 = wc / ta;
9        double X2 = re / ta;
10        double X3 = ebit / ta;
11        double X4 = mve / tl;
12        double X5 = sales / ta;
13        return 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5;
14    }
15
16    static void Main()
17    {
18        double zScore = CalculateZScore(50, 200, 100, 500, 400, 600, 800);
19        Console.WriteLine($"Altman Z-Score: {zScore:F2}");
20    }
21}
22

Go

1// Go Altman Z-Score Calculation
2package main
3
4import (
5    "fmt"
6)
7
8func calculateZScore(wc, re, ebit, mve, tl, sales, ta float64) float64 {
9    X1 := wc / ta
10    X2 := re / ta
11    X3 := ebit / ta
12    X4 := mve / tl
13    X5 := sales / ta
14    return 1.2*X1 + 1.4*X2 + 3.3*X3 + 0.6*X4 + X5
15}
16
17func main() {
18    zScore := calculateZScore(50, 200, 100, 500, 400, 600, 800)
19    fmt.Printf("Altman Z-Score: %.2f\n", zScore)
20}
21

Swift

1// Swift Altman Z-Score Calculation
2func calculateZScore(wc: Double, re: Double, ebit: Double, mve: Double, tl: Double, sales: Double, ta: Double) -> Double {
3    let X1 = wc / ta
4    let X2 = re / ta
5    let X3 = ebit / ta
6    let X4 = mve / tl
7    let X5 = sales / ta
8    return 1.2 * X1 + 1.4 * X2 + 3.3 * X3 + 0.6 * X4 + X5
9}
10
11// Example usage:
12let zScore = calculateZScore(wc: 50, re: 200, ebit: 100, mve: 500, tl: 400, sales: 600, ta: 800)
13print(String(format: "Altman Z-Score: %.2f", zScore))
14

Frequently Asked Questions (FAQ)

What is a good Altman Z-Score?

A good Altman Z-Score is above 2.99, placing a company in the "Safe Zone" with low bankruptcy risk. Scores between 1.81 and 2.99 indicate moderate risk (Grey Zone), while scores below 1.81 signal high bankruptcy risk (Distress Zone).

How accurate is the Altman Z-Score in predicting bankruptcy?

The Altman Z-Score accuracy is approximately 80-90% for predicting bankruptcy within two years for publicly traded manufacturing companies. However, accuracy varies by industry, company size, and economic conditions.

Can I use the Altman Z-Score for private companies?

Yes, but use the Z'-Score model (modified Altman Z-Score) for private manufacturing companies or the Z''-Score model for private non-manufacturing and emerging market companies. These variants adjust the formula coefficients and ratios for non-public firms.

What does a negative Altman Z-Score mean?

A negative Z-Score indicates severe financial distress, typically caused by negative working capital, retained earnings, or EBIT. Companies with negative scores face very high bankruptcy risk and require immediate corrective action.

How often should I calculate the Altman Z-Score?

Calculate the Altman Z-Score quarterly or annually when new financial statements are released. For high-risk companies or during economic downturns, monthly monitoring may be appropriate to detect rapid deterioration.

What are the limitations of the Altman Z-Score?

Key limitations include:

Best suited for publicly traded manufacturing companies
Does not account for industry-specific factors or economic conditions
Can be manipulated through creative accounting
Less reliable for service, technology, or financial sector companies
Historical model may not capture modern business risks

How is the Altman Z-Score different from credit ratings?

While credit ratings (like S&P or Moody's) provide qualitative assessments combining quantitative and subjective factors, the Altman Z-Score is a purely quantitative, formula-based metric. Z-Scores offer objective, real-time bankruptcy risk assessment using financial ratios.

Can the Altman Z-Score be used for startups?

The Altman Z-Score is not ideal for startups because they often have negative earnings, limited retained earnings, and minimal operating history. The model works best for established companies with consistent financial data spanning multiple years.

References

Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4), 589–609.
Altman Z-Score. Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Altman_Z-score
Investopedia - Altman Z-Score. Retrieved from https://www.investopedia.com/terms/a/altman.asp

Calculate Your Company's Bankruptcy Risk Today

Use our free Altman Z-Score calculator above to assess financial health and predict bankruptcy risk in seconds. Enter your company's financial data to receive an instant Z-Score analysis with interpretation and risk zone classification.

Altman Z-Score Calculator - Predict Bankruptcy Risk Free

Altman Z-Score

Input Values

Result

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