Magyar Telekom Beneish M-Score Historical Data
The historical data trend for Magyar Telekom'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.
Magyar Telekom Beneish M-Score Chart
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Magyar Telekom Annual Data
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Trend |
Dec14 |
Dec15 |
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Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.97 |
-2.93 |
-3.02 |
-2.86 |
-2.82 |
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Magyar Telekom Quarterly Data
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Jun19 |
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Mar21 |
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Mar24 |
| Beneish M-Score |
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-2.82 |
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Competitive Comparison of Magyar Telekom's Beneish M-Score
For the Telecom Services subindustry, Magyar Telekom'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.
Magyar Telekom's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, Magyar Telekom's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Magyar Telekom's Beneish M-Score falls into.
Magyar Telekom 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 Magyar Telekom 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 * 1.0198 | + | 0.528 * 0.9748 | + | 0.404 * 0.9369 | + | 0.892 * 1.1375 | + | 0.115 * 0.9969 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9259 | + | 4.679 * -0.098235 | - | 0.327 * 0.9698 |
| = | -2.82 |
* 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 $621 Mil.
Revenue was $2,380 Mil.
Gross Profit was $1,382 Mil.
Total Current Assets was $799 Mil.
Total Assets was $4,102 Mil.
Property, Plant and Equipment(Net PPE) was $1,678 Mil.
Depreciation, Depletion and Amortization(DDA) was $390 Mil.
Selling, General, & Admin. Expense(SGA) was $28 Mil.
Total Current Liabilities was $973 Mil.
Long-Term Debt & Capital Lease Obligation was $634 Mil.
Net Income was $221 Mil.
Gross Profit was $0 Mil.
Cash Flow from Operations was $624 Mil.
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Total Receivables was $535 Mil.
Revenue was $2,092 Mil.
Gross Profit was $1,184 Mil.
Total Current Assets was $676 Mil.
Total Assets was $4,081 Mil.
Property, Plant and Equipment(Net PPE) was $1,680 Mil.
Depreciation, Depletion and Amortization(DDA) was $389 Mil.
Selling, General, & Admin. Expense(SGA) was $27 Mil.
Total Current Liabilities was $860 Mil.
Long-Term Debt & Capital Lease Obligation was $789 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) |
| = | (620.917 / 2380.174) | / | (535.254 / 2092.372) |
| = | 0.26087 | / | 0.255812 |
| | = | 1.0198 |
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) |
| = | (1184.012 / 2092.372) | / | (1381.67 / 2380.174) |
| = | 0.565871 | / | 0.580491 |
| | = | 0.9748 |
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 - (799.422 + 1678.148) / 4102.057) | / | (1 - (676.265 + 1679.816) / 4081.281) |
| = | 0.396018 | / | 0.42271 |
| | = | 0.9369 |
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 |
| = | 2380.174 | / | 2092.372 |
| | = | 1.1375 |
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)) |
| = | (388.866 / (388.866 + 1679.816)) | / | (389.987 / (389.987 + 1678.148)) |
| = | 0.187978 | / | 0.188569 |
| | = | 0.9969 |
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) |
| = | (28.149 / 2380.174) | / | (26.725 / 2092.372) |
| = | 0.011826 | / | 0.012773 |
| | = | 0.9259 |
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) |
| = | ((634.222 + 972.905) / 4102.057) | / | ((788.72 + 860.086) / 4081.281) |
| = | 0.391786 | / | 0.403992 |
| | = | 0.9698 |
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 |
| = | (221.242 - 0 | - | 624.207) | / | 4102.057 |
| | = | -0.098235 |
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.
Magyar Telekom has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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