United States Steel Beneish M-Score Historical Data
The historical data trend for United States Steel'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.
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United States Steel Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.46 |
-1.81 |
-1.82 |
-2.79 |
-2.55 |
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United States Steel 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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|
|
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|
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-2.79 |
-2.62 |
-2.57 |
-2.65 |
-2.55 |
Competitive Comparison
For the Steel subindustry, United States Steel'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.
United States Steel Beneish M-Score Distribution
For the Steel industry and Basic Materials sector, United States Steel's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where United States Steel's Beneish M-Score falls into.
United States Steel 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 United States Steel 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 * 1.1048 | + | 0.528 * 1.6333 | + | 0.404 * 0.9682 | + | 0.892 * 0.857 | + | 0.115 * 1.0457 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3853 | + | 4.679 * -0.066843 | - | 0.327 * 0.9661 |
| = | -2.55 |
* 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 $1,548 Mil.
Revenue was 4144 + 4431 + 5008 + 4470 = $18,053 Mil.
Gross Profit was 293 + 593 + 847 + 517 = $2,250 Mil.
Total Current Assets was $6,943 Mil.
Total Assets was $20,451 Mil.
Property, Plant and Equipment(Net PPE) was $10,502 Mil.
Depreciation, Depletion and Amortization(DDA) was $916 Mil.
Selling, General, & Admin. Expense(SGA) was $501 Mil.
Total Current Liabilities was $3,948 Mil.
Long-Term Debt & Capital Lease Obligation was $4,153 Mil.
Net Income was -80 + 299 + 477 + 199 = $895 Mil.
Non Operating Income was -60 + 81 + 85 + 56 = $162 Mil.
Cash Flow from Operations was 389 + 817 + 713 + 181 = $2,100 Mil.
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Total Receivables was $1,635 Mil.
Revenue was 4338 + 5203 + 6290 + 5234 = $21,065 Mil.
Gross Profit was 404 + 844 + 1629 + 1411 = $4,288 Mil.
Total Current Assets was $7,866 Mil.
Total Assets was $19,458 Mil.
Property, Plant and Equipment(Net PPE) was $8,638 Mil.
Depreciation, Depletion and Amortization(DDA) was $791 Mil.
Selling, General, & Admin. Expense(SGA) was $422 Mil.
Total Current Liabilities was $3,959 Mil.
Long-Term Debt & Capital Lease Obligation was $4,019 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) |
| = | (1548 / 18053) | / | (1635 / 21065) |
| = | 0.085748 | / | 0.077617 |
| | = | 1.1048 |
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) |
| = | (4288 / 21065) | / | (2250 / 18053) |
| = | 0.20356 | / | 0.124633 |
| | = | 1.6333 |
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 - (6943 + 10502) / 20451) | / | (1 - (7866 + 8638) / 19458) |
| = | 0.146985 | / | 0.151814 |
| | = | 0.9682 |
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 |
| = | 18053 | / | 21065 |
| | = | 0.857 |
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)) |
| = | (791 / (791 + 8638)) | / | (916 / (916 + 10502)) |
| = | 0.08389 | / | 0.080224 |
| | = | 1.0457 |
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) |
| = | (501 / 18053) | / | (422 / 21065) |
| = | 0.027752 | / | 0.020033 |
| | = | 1.3853 |
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) |
| = | ((4153 + 3948) / 20451) | / | ((4019 + 3959) / 19458) |
| = | 0.396118 | / | 0.410011 |
| | = | 0.9661 |
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 |
| = | (895 - 162 | - | 2100) | / | 20451 |
| | = | -0.066843 |
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.
United States Steel has a M-score of -2.55 suggests that the company is unlikely to be a manipulator.
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