Grover G-Score Calculator
Evaluate corporate insolvency probability, liquidity adequacy, and operating profitability using Jeffrey S. Grover's (2001) discriminant bankruptcy model.
Financial Balance Sheet & Income Parameters
Solvency Assessment & G-Score Breakdown
Safe ZoneModel Components & Discriminant Decomposition
| Variable | Metric Ratio | Weight | Contribution | % of Total Score |
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EBIT Margin vs Working Capital Sensitivity Matrix (G-Score)
Explore how simultaneous shifts in operating profitability (EBIT / Total Assets) and short-term liquidity (Working Capital / Total Assets) alter the company's Grover G-Score solvency rating.
Understanding Jeffrey Grover's Bankruptcy Prediction Architecture
In 2001, financial researcher Jeffrey S. Grover published a landmark re-estimation of corporate failure prediction models. Addressing structural limitations in Edward Altman's 1968 Z-Score—which relied on 1946–1965 manufacturing cohorts and heavily penalized asset-light and service corporations through capital turnover and market-equity ratios—Grover isolated the three most statistically significant variables across modern corporate failures:
1. Working Capital / Assets (X1)
Measures short-term balance sheet liquidity. A shrinking or negative ratio signals that operational liabilities outstrip current liquid resources, heralding acute cash-flow insolvency.
2. EBIT / Total Assets (X3)
Evaluates core operating profitability unclouded by tax shielding or debt capital structures. Carrying the heaviest positive weighting (+0.090), operational earnings power represents the fundamental defense against insolvency.
3. Net Income / Total Assets (X4)
Measures bottom-line net return on assets. Paired with X3, this variable acts as an empirical dampener, penalizing firms where excessive debt service or non-operating losses eliminate equity returns.
The Linear Discriminant Equation
A G-Score greater than or equal to +0.01 indicates financial stability. Scores below -0.02 warn of impending bankruptcy within 1 to 3 years. The intermediate range (-0.02 to +0.01) represents an ambiguous gray zone warranting rigorous operational audits.
Credit Risk & Solvency Knowledge Check
Frequently Asked Questions
What is the Grover G-Score and how is it calculated?
The Grover G-Score is an empirical bankruptcy prediction model developed by Jeffrey S. Grover in 2001. Redesigning and re-estimating Edward Altman's 1968 Z-Score framework using modern corporate filing data, the model computes: G = 0.033*X1 + 0.090*X3 - 0.022*X4 + 0.284, where X1 is Working Capital divided by Total Assets, X3 is Earnings Before Interest and Taxes (EBIT) divided by Total Assets, and X4 is Net Income divided by Total Assets.
What are the decision thresholds for the Grover G-Score?
The Grover model defines three distinct credit classifications: A G-Score of +0.01 or higher classifies the company as financially sound (Safe Zone). A G-Score of -0.02 or lower classifies the company as distressed with a high probability of bankruptcy within 1 to 3 years (Bankrupt/Distress Zone). Scores falling strictly between -0.02 and +0.01 represent an indeterminate Gray Zone requiring qualitative audit review.
Why is the coefficient on Net Income to Assets (X4) negative in the Grover formula?
In Grover's statistical discriminant analysis, operating profitability (EBIT/TA, X3) receives a strong positive loading of +0.090. Because Net Income (X4) reflects post-tax earnings after interest and non-operating charges, multicollinearity between operating earnings and net income results in a negative balancing coefficient (-0.022). This dampens misleading one-off tax benefits or non-operating gains while heavily penalizing companies with persistent operational operating losses.
How does the Grover G-Score compare to Altman's Z-Score and Springate's Model?
While Altman's original 1968 Z-Score utilized five financial ratios and Springate (1978) utilized four, Grover demonstrated that a lean, three-ratio discriminant function re-estimated on modern industrial and service corporations achieved superior out-of-sample accuracy, successfully classifying over 85% of bankruptcies up to three years before legal insolvency while maintaining low Type I and Type II error rates.