TIM Beneish M-Score Historical Data
The historical data trend for TIM'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.
TIM Beneish M-Score Chart
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TIM Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.61 |
-3.32 |
-3.21 |
-3.05 |
-3.12 |
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TIM Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.19 |
-3.12 |
-3.13 |
-3.15 |
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Competitive Comparison of TIM's Beneish M-Score
For the Telecom Services subindustry, TIM'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.
TIM's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, TIM's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where TIM's Beneish M-Score falls into.
TIM 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 TIM 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 * | + | 0.528 * | + | 0.404 * | + | 0.892 * | + | 0.115 * |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * | + | 4.679 * | - | 0.327 * |
| = | |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $1,003 Mil.
Revenue was 1159.114 + 1170.149 + 1224.051 + 1280.697 = $4,834 Mil.
Gross Profit was 624.718 + 628.899 + 631.079 + 686.107 = $2,571 Mil.
Total Current Assets was $2,032 Mil.
Total Assets was $9,848 Mil.
Property, Plant and Equipment(Net PPE) was $4,057 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,359 Mil.
Selling, General, & Admin. Expense(SGA) was $1,238 Mil.
Total Current Liabilities was $2,099 Mil.
Long-Term Debt & Capital Lease Obligation was $2,427 Mil.
Net Income was 145.369 + 145.044 + 104.306 + 220.929 = $616 Mil.
Non Operating Income was -3.617 + -0.014 + -39.283 + 25.316 = $-18 Mil.
Cash Flow from Operations was 628.043 + 498.785 + 330.473 + 989.63 = $2,447 Mil.
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Total Receivables was $0 Mil.
Revenue was 1226.096 + 1207.998 + 1082.854 + 1110.376 = $4,627 Mil.
Gross Profit was 651.282 + 603.812 + 543.037 + 563.306 = $2,361 Mil.
Total Current Assets was $0 Mil.
Total Assets was $0 Mil.
Property, Plant and Equipment(Net PPE) was $0 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,429 Mil.
Selling, General, & Admin. Expense(SGA) was $1,264 Mil.
Total Current Liabilities was $0 Mil.
Long-Term Debt & Capital Lease Obligation was $0 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) |
| = | (1003.137 / 4834.011) | / | (0 / 4627.324) |
| = | 0.207516 | / | 0 |
| | = | |
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) |
| = | (2361.437 / 4627.324) | / | (2570.803 / 4834.011) |
| = | 0.510325 | / | 0.531816 |
| | = | |
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 - (2031.712 + 4057.086) / 9847.937) | / | (1 - (0 + 0) / 0) |
| = | 0.381718 | / | |
| | = | |
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 |
| = | 4834.011 | / | 4627.324 |
| | = | |
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)) |
| = | (1428.858 / (1428.858 + 0)) | / | (1358.757 / (1358.757 + 4057.086)) |
| = | 1 | / | 0.250886 |
| | = | |
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) |
| = | (1238.013 / 4834.011) | / | (1264.419 / 4627.324) |
| = | 0.256105 | / | 0.273251 |
| | = | |
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) |
| = | ((2426.666 + 2099.311) / 9847.937) | / | ((0 + 0) / 0) |
| = | 0.459586 | / | |
| | = | |
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 |
| = | (615.648 - -17.598 | - | 2446.931) | / | 9847.937 |
| | = | -0.184169 |
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.
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