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 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
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-2.89 |
-1.95 |
-2.52 |
-2.69 |
-2.81 |
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T-Mobile US 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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-2.69 |
-2.75 |
-2.78 |
-2.82 |
-2.81 |
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 * 0.9684 | + | 0.528 * 0.8851 | + | 0.404 * 1.0143 | + | 0.892 * 0.9873 | + | 0.115 * 1.0158 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.999 | + | 4.679 * -0.049764 | - | 0.327 * 1.0086 |
| = | -2.81 |
* 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 $9,148 Mil.
Revenue was 20478 + 19252 + 19196 + 19632 = $78,558 Mil.
Gross Profit was 12078 + 12117 + 12192 + 11983 = $48,370 Mil.
Total Current Assets was $19,015 Mil.
Total Assets was $207,682 Mil.
Property, Plant and Equipment(Net PPE) was $70,837 Mil.
Depreciation, Depletion and Amortization(DDA) was $12,818 Mil.
Selling, General, & Admin. Expense(SGA) was $21,311 Mil.
Total Current Liabilities was $20,928 Mil.
Long-Term Debt & Capital Lease Obligation was $104,652 Mil.
Net Income was 2014 + 2142 + 2221 + 1940 = $8,317 Mil.
Non Operating Income was 12 + 41 + -11 + 51 = $93 Mil.
Cash Flow from Operations was 4859 + 5294 + 4355 + 4051 = $18,559 Mil.
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Total Receivables was $9,568 Mil.
Revenue was 20273 + 19477 + 19701 + 20120 = $79,571 Mil.
Gross Profit was 11602 + 10783 + 10533 + 10447 = $43,365 Mil.
Total Current Assets was $19,067 Mil.
Total Assets was $211,338 Mil.
Property, Plant and Equipment(Net PPE) was $74,058 Mil.
Depreciation, Depletion and Amortization(DDA) was $13,651 Mil.
Selling, General, & Admin. Expense(SGA) was $21,607 Mil.
Total Current Liabilities was $24,742 Mil.
Long-Term Debt & Capital Lease Obligation was $101,955 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) |
| = | (9148 / 78558) | / | (9568 / 79571) |
| = | 0.116449 | / | 0.120245 |
| | = | 0.9684 |
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) |
| = | (43365 / 79571) | / | (48370 / 78558) |
| = | 0.544985 | / | 0.615723 |
| | = | 0.8851 |
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 - (19015 + 70837) / 207682) | / | (1 - (19067 + 74058) / 211338) |
| = | 0.567358 | / | 0.559355 |
| | = | 1.0143 |
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 |
| = | 78558 | / | 79571 |
| | = | 0.9873 |
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)) |
| = | (13651 / (13651 + 74058)) | / | (12818 / (12818 + 70837)) |
| = | 0.15564 | / | 0.153225 |
| | = | 1.0158 |
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) |
| = | (21311 / 78558) | / | (21607 / 79571) |
| = | 0.271277 | / | 0.271544 |
| | = | 0.999 |
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) |
| = | ((104652 + 20928) / 207682) | / | ((101955 + 24742) / 211338) |
| = | 0.604674 | / | 0.599499 |
| | = | 1.0086 |
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 |
| = | (8317 - 93 | - | 18559) | / | 207682 |
| | = | -0.049764 |
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 -2.81 suggests that the company is unlikely to be a manipulator.
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