China Mobile Beneish M-Score Historical Data
The historical data trend for China Mobile'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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China Mobile Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-1.65 |
-2.42 |
-2.49 |
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China Mobile Quarterly Data
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Jun18 |
Dec18 |
Jun19 |
Dec19 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.95 |
-2.63 |
-2.78 |
-2.49 |
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Competitive Comparison
For the Telecom Services subindustry, China Mobile'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.
China Mobile Beneish M-Score Distribution
For the Telecommunication Services industry and Communication Services sector, China Mobile's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where China Mobile's Beneish M-Score falls into.
China Mobile 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 China Mobile 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 * 1.1643 | + | 0.528 * 1.0097 | + | 0.404 * 1.0223 | + | 0.892 * 1.0769 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9825 | + | 4.679 * -0.053151 | - | 0.327 * 0.9891 |
| = | -2.49 |
* 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 ¥87,835 Mil.
Revenue was 233749 + 244841 + 279973 + 250746 = ¥1,009,309 Mil.
Gross Profit was 374654 + -86908 + 248532 + 61329 = ¥597,607 Mil.
Total Current Assets was ¥498,104 Mil.
Total Assets was ¥1,992,657 Mil.
Property, Plant and Equipment(Net PPE) was ¥883,912 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥52,564 Mil.
Total Current Liabilities was ¥558,565 Mil.
Long-Term Debt & Capital Lease Obligation was ¥67,759 Mil.
Net Income was 26260 + 29333 + 48106 + 28067 = ¥131,766 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0 Mil.
Cash Flow from Operations was 0 + 77153 + 85320 + 75205 = ¥237,678 Mil.
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Total Receivables was ¥70,054 Mil.
Revenue was 213772 + 226553 + 269614 + 227320 = ¥937,259 Mil.
Gross Profit was 359657 + -89163 + 235213 + 54627 = ¥560,334 Mil.
Total Current Assets was ¥456,371 Mil.
Total Assets was ¥1,935,538 Mil.
Property, Plant and Equipment(Net PPE) was ¥898,957 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥49,682 Mil.
Total Current Liabilities was ¥533,337 Mil.
Long-Term Debt & Capital Lease Obligation was ¥81,741 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) |
| = | (87835 / 1009309) | / | (70054 / 937259) |
| = | 0.087025 | / | 0.074743 |
| | = | 1.1643 |
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) |
| = | (560334 / 937259) | / | (597607 / 1009309) |
| = | 0.597843 | / | 0.592095 |
| | = | 1.0097 |
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 - (498104 + 883912) / 1992657) | / | (1 - (456371 + 898957) / 1935538) |
| = | 0.306446 | / | 0.299767 |
| | = | 1.0223 |
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 |
| = | 1009309 | / | 937259 |
| | = | 1.0769 |
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)) |
| = | (0 / (0 + 898957)) | / | (0 / (0 + 883912)) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (52564 / 1009309) | / | (49682 / 937259) |
| = | 0.052079 | / | 0.053008 |
| | = | 0.9825 |
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) |
| = | ((67759 + 558565) / 1992657) | / | ((81741 + 533337) / 1935538) |
| = | 0.314316 | / | 0.317781 |
| | = | 0.9891 |
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 |
| = | (131766 - 0 | - | 237678) | / | 1992657 |
| | = | -0.053151 |
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.
China Mobile has a M-score of -2.49 suggests that the company is unlikely to be a manipulator.
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