Griffon Beneish M-Score Historical Data
The historical data trend for Griffon's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Griffon Beneish M-Score Chart
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Griffon Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.75 |
-2.55 |
-2.54 |
-1.89 |
-3.19 |
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Griffon Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.26 |
-3.00 |
-3.24 |
-3.19 |
-3.31 |
Competitive Comparison of Griffon's Beneish M-Score
For the Conglomerates subindustry, Griffon's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Griffon's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, Griffon's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Griffon's Beneish M-Score falls into.
Griffon Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Griffon for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.9269 | + | 0.528 * 0.9734 | + | 0.404 * 1.02 | + | 0.892 * 0.9218 | + | 0.115 * 1.0202 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1 | + | 4.679 * -0.136179 | - | 0.327 * 1.1125 |
| = | -3.31 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $300 Mil.
Revenue was 643.153 + 641.385 + 683.43 + 710.984 = $2,679 Mil.
Gross Profit was 236.641 + 245.88 + 274.624 + 194.492 = $952 Mil.
Total Current Assets was $963 Mil.
Total Assets was $2,393 Mil.
Property, Plant and Equipment(Net PPE) was $445 Mil.
Depreciation, Depletion and Amortization(DDA) was $63 Mil.
Selling, General, & Admin. Expense(SGA) was $649 Mil.
Total Current Liabilities was $392 Mil.
Long-Term Debt & Capital Lease Obligation was $1,583 Mil.
Net Income was 42.177 + 41.965 + 49.205 + -62.255 = $71 Mil.
Non Operating Income was 0.459 + -1.507 + -0.61 + -99.707 = $-101 Mil.
Cash Flow from Operations was 143.132 + 122.567 + 147.166 + 85.511 = $498 Mil.
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Total Receivables was $351 Mil.
Revenue was 649.384 + 708.943 + 768.179 + 779.617 = $2,906 Mil.
Gross Profit was 233.825 + 249.8 + 260.601 + 260.643 = $1,005 Mil.
Total Current Assets was $1,183 Mil.
Total Assets was $2,777 Mil.
Property, Plant and Equipment(Net PPE) was $473 Mil.
Depreciation, Depletion and Amortization(DDA) was $69 Mil.
Selling, General, & Admin. Expense(SGA) was $640 Mil.
Total Current Liabilities was $391 Mil.
Long-Term Debt & Capital Lease Obligation was $1,668 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (299.594 / 2678.952) | / | (350.625 / 2906.123) |
| = | 0.111833 | / | 0.12065 |
| | = | 0.9269 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (1004.869 / 2906.123) | / | (951.637 / 2678.952) |
| = | 0.345776 | / | 0.355227 |
| | = | 0.9734 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (962.606 + 445.229) / 2393.313) | / | (1 - (1182.765 + 473.304) / 2777.238) |
| = | 0.411763 | / | 0.403699 |
| | = | 1.02 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 2678.952 | / | 2906.123 |
| | = | 0.9218 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (68.69 / (68.69 + 473.304)) | / | (63.155 / (63.155 + 445.229)) |
| = | 0.126736 | / | 0.124227 |
| | = | 1.0202 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (648.784 / 2678.952) | / | (639.807 / 2906.123) |
| = | 0.242178 | / | 0.220158 |
| | = | 1.1 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((1582.578 + 391.679) / 2393.313) | / | ((1668.345 + 390.859) / 2777.238) |
| = | 0.824905 | / | 0.741458 |
| | = | 1.1125 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (71.092 - -101.365 | - | 498.376) | / | 2393.313 |
| | = | -0.136179 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Griffon has a M-score of -3.31 suggests that the company is unlikely to be a manipulator.
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