T-Mobile US Beneish M-Score Historical Data
The historical data trend for T-Mobile US'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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T-Mobile US Annual Data
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Trend |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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|
|
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-2.33 |
-2.39 |
-2.92 |
-1.95 |
-2.52 |
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T-Mobile US Quarterly Data
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Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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|
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-2.31 |
-2.49 |
-2.52 |
-2.47 |
-2.61 |
Competitive Comparison
For the Telecom Services subindustry, T-Mobile US'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.
T-Mobile US Beneish M-Score Distribution
For the Telecommunication Services industry and Communication Services sector, T-Mobile US's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where T-Mobile US's Beneish M-Score falls into.
T-Mobile US 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 T-Mobile US 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 * 1.1018 | + | 0.528 * 1.0657 | + | 0.404 * 1.016 | + | 0.892 * 1.0114 | + | 0.115 * 1.1338 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1047 | + | 4.679 * -0.0584 | - | 0.327 * 0.9998 |
| = | -2.61 |
* 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 (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $9,595 Mil.
Revenue was 19701 + 20120 + 20785 + 19624 = $80,230 Mil.
Gross Profit was 10533 + 10447 + 10333 + 10941 = $42,254 Mil.
Total Current Assets was $17,476 Mil.
Total Assets was $209,463 Mil.
Property, Plant and Equipment(Net PPE) was $73,943 Mil.
Depreciation, Depletion and Amortization(DDA) was $15,093 Mil.
Selling, General, & Admin. Expense(SGA) was $21,522 Mil.
Total Current Liabilities was $20,622 Mil.
Long-Term Debt & Capital Lease Obligation was $100,560 Mil.
Net Income was -108 + 713 + 422 + 691 = $1,718 Mil.
Non Operating Income was -498 + -11 + -13 + -60 = $-582 Mil.
Cash Flow from Operations was 4209 + 3845 + 3000 + 3477 = $14,531 Mil.
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Total Receivables was $8,610 Mil.
Revenue was 19950 + 19759 + 20341 + 19272 = $79,322 Mil.
Gross Profit was 11006 + 11233 + 10689 + 11591 = $44,519 Mil.
Total Current Assets was $20,570 Mil.
Total Assets was $204,124 Mil.
Property, Plant and Equipment(Net PPE) was $70,335 Mil.
Depreciation, Depletion and Amortization(DDA) was $16,735 Mil.
Selling, General, & Admin. Expense(SGA) was $19,262 Mil.
Total Current Liabilities was $21,837 Mil.
Long-Term Debt & Capital Lease Obligation was $96,278 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) |
| = | (9595 / 80230) | / | (8610 / 79322) |
| = | 0.11959367 | / | 0.10854492 |
| | = | 1.1018 |
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) |
| = | (44519 / 79322) | / | (42254 / 80230) |
| = | 0.56124404 | / | 0.52666085 |
| | = | 1.0657 |
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 - (17476 + 73943) / 209463) | / | (1 - (20570 + 70335) / 204124) |
| = | 0.56355538 | / | 0.55465795 |
| | = | 1.016 |
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 |
| = | 80230 | / | 79322 |
| | = | 1.0114 |
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)) |
| = | (16735 / (16735 + 70335)) | / | (15093 / (15093 + 73943)) |
| = | 0.19220168 | / | 0.1695157 |
| | = | 1.1338 |
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) |
| = | (21522 / 80230) | / | (19262 / 79322) |
| = | 0.26825377 | / | 0.24283301 |
| | = | 1.1047 |
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) |
| = | ((100560 + 20622) / 209463) | / | ((96278 + 21837) / 204124) |
| = | 0.57853654 | / | 0.57864337 |
| | = | 0.9998 |
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 |
| = | (1718 - -582 | - | 14531) | / | 209463 |
| | = | -0.0584 |
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.
T-Mobile US has a M-score of -2.61 suggests that the company is unlikely to be a manipulator.
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