Telecom Argentina Beneish M-Score Historical Data
The historical data trend for Telecom Argentina'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.
Telecom Argentina Beneish M-Score Chart
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Telecom Argentina Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.48 |
-3.09 |
-3.42 |
-0.47 |
-2.78 |
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Telecom Argentina 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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-2.69 |
-2.78 |
1.80 |
3.31 |
4.79 |
Competitive Comparison of Telecom Argentina's Beneish M-Score
For the Telecom Services subindustry, Telecom Argentina'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.
Telecom Argentina's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, Telecom Argentina's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Telecom Argentina's Beneish M-Score falls into.
Telecom Argentina 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 Telecom Argentina 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 * 9.3339 | + | 0.528 * 1.0093 | + | 0.404 * 1.0804 | + | 0.892 * 0.3541 | + | 0.115 * 4.3672 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9416 | + | 4.679 * -0.058634 | - | 0.327 * 0.944 |
| = | 4.79 |
* 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 ARS291,501 Mil.
Revenue was 983141 + 856084 + 683916 + -1125993 = ARS1,397,148 Mil.
Gross Profit was 724040 + 627576 + 497478 + -831346 = ARS1,017,748 Mil.
Total Current Assets was ARS717,760 Mil.
Total Assets was ARS10,193,592 Mil.
Property, Plant and Equipment(Net PPE) was ARS4,532,068 Mil.
Depreciation, Depletion and Amortization(DDA) was ARS557,083 Mil.
Selling, General, & Admin. Expense(SGA) was ARS407,708 Mil.
Total Current Liabilities was ARS1,791,510 Mil.
Long-Term Debt & Capital Lease Obligation was ARS1,748,897 Mil.
Net Income was -16361 + 54608 + 672260 + -508960 = ARS201,547 Mil.
Non Operating Income was 22591 + 241616 + 893821 + -511577 = ARS646,451 Mil.
Cash Flow from Operations was 150347 + 157430 + 171229 + -326214 = ARS152,792 Mil.
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Total Receivables was ARS88,199 Mil.
Revenue was 1030218 + 933838 + 833213 + 1148513 = ARS3,945,782 Mil.
Gross Profit was 759141 + 672982 + 624240 + 844741 = ARS2,901,104 Mil.
Total Current Assets was ARS258,831 Mil.
Total Assets was ARS3,385,351 Mil.
Property, Plant and Equipment(Net PPE) was ARS1,606,801 Mil.
Depreciation, Depletion and Amortization(DDA) was ARS1,471,723 Mil.
Selling, General, & Admin. Expense(SGA) was ARS1,222,853 Mil.
Total Current Liabilities was ARS572,268 Mil.
Long-Term Debt & Capital Lease Obligation was ARS673,296 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) |
| = | (291501 / 1397148) | / | (88199 / 3945782) |
| = | 0.20864 | / | 0.022353 |
| | = | 9.3339 |
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) |
| = | (2901104 / 3945782) | / | (1017748 / 1397148) |
| = | 0.735242 | / | 0.728447 |
| | = | 1.0093 |
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 - (717760 + 4532068) / 10193592) | / | (1 - (258831 + 1606801) / 3385351) |
| = | 0.484987 | / | 0.44891 |
| | = | 1.0804 |
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 |
| = | 1397148 | / | 3945782 |
| | = | 0.3541 |
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)) |
| = | (1471723 / (1471723 + 1606801)) | / | (557083 / (557083 + 4532068)) |
| = | 0.478061 | / | 0.109465 |
| | = | 4.3672 |
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) |
| = | (407708 / 1397148) | / | (1222853 / 3945782) |
| = | 0.291814 | / | 0.309914 |
| | = | 0.9416 |
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) |
| = | ((1748897 + 1791510) / 10193592) | / | ((673296 + 572268) / 3385351) |
| = | 0.347317 | / | 0.367928 |
| | = | 0.944 |
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 |
| = | (201547 - 646451 | - | 152792) | / | 10193592 |
| | = | -0.058634 |
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.
Telecom Argentina has a M-score of 4.79 signals that the company is likely to be a manipulator.
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