Federal Signal Beneish M-Score Historical Data
The historical data trend for Federal Signal'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.
Federal Signal Beneish M-Score Chart
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Federal Signal Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.36 |
-2.64 |
-2.41 |
-2.13 |
-2.51 |
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Federal Signal 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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-2.13 |
-2.16 |
-2.28 |
-2.24 |
-2.51 |
Competitive Comparison of Federal Signal's Beneish M-Score
For the Pollution & Treatment Controls subindustry, Federal Signal'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.
Federal Signal's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Federal Signal's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Federal Signal's Beneish M-Score falls into.
Federal Signal 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 Federal Signal 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 * 0.8923 | + | 0.528 * 0.9198 | + | 0.404 * 0.9737 | + | 0.892 * 1.2007 | + | 0.115 * 1.0021 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0192 | + | 4.679 * -0.021475 | - | 0.327 * 0.8475 |
| = | -2.51 |
* 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 $186 Mil.
Revenue was 448.4 + 446.4 + 442.4 + 385.5 = $1,723 Mil.
Gross Profit was 119.4 + 117.7 + 117.3 + 95.8 = $450 Mil.
Total Current Assets was $570 Mil.
Total Assets was $1,621 Mil.
Property, Plant and Equipment(Net PPE) was $347 Mil.
Depreciation, Depletion and Amortization(DDA) was $60 Mil.
Selling, General, & Admin. Expense(SGA) was $210 Mil.
Total Current Liabilities was $196 Mil.
Long-Term Debt & Capital Lease Obligation was $309 Mil.
Net Income was 46.4 + 43.3 + 40.3 + 27.4 = $157 Mil.
Non Operating Income was 1.3 + -1 + -1.7 + -0.8 = $-2 Mil.
Cash Flow from Operations was 103.4 + 48 + 35.9 + 7.1 = $194 Mil.
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Total Receivables was $174 Mil.
Revenue was 391.5 + 346.4 + 366.7 + 330.2 = $1,435 Mil.
Gross Profit was 96.6 + 82.8 + 89.8 + 75.7 = $345 Mil.
Total Current Assets was $531 Mil.
Total Assets was $1,524 Mil.
Property, Plant and Equipment(Net PPE) was $313 Mil.
Depreciation, Depletion and Amortization(DDA) was $55 Mil.
Selling, General, & Admin. Expense(SGA) was $172 Mil.
Total Current Liabilities was $181 Mil.
Long-Term Debt & Capital Lease Obligation was $380 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) |
| = | (186.2 / 1722.7) | / | (173.8 / 1434.8) |
| = | 0.108086 | / | 0.121132 |
| | = | 0.8923 |
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) |
| = | (344.9 / 1434.8) | / | (450.2 / 1722.7) |
| = | 0.240382 | / | 0.261334 |
| | = | 0.9198 |
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 - (570.2 + 346.6) / 1620.5) | / | (1 - (531.4 + 313.1) / 1524.3) |
| = | 0.434249 | / | 0.445975 |
| | = | 0.9737 |
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 |
| = | 1722.7 | / | 1434.8 |
| | = | 1.2007 |
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)) |
| = | (54.7 / (54.7 + 313.1)) | / | (60.4 / (60.4 + 346.6)) |
| = | 0.148722 | / | 0.148403 |
| | = | 1.0021 |
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) |
| = | (210.1 / 1722.7) | / | (171.7 / 1434.8) |
| = | 0.12196 | / | 0.119668 |
| | = | 1.0192 |
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) |
| = | ((309.2 + 195.8) / 1620.5) | / | ((380 + 180.5) / 1524.3) |
| = | 0.311632 | / | 0.36771 |
| | = | 0.8475 |
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 |
| = | (157.4 - -2.2 | - | 194.4) | / | 1620.5 |
| | = | -0.021475 |
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.
Federal Signal has a M-score of -2.51 suggests that the company is unlikely to be a manipulator.
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