PAO Sovcomflot Beneish M-Score Historical Data
The historical data trend for PAO Sovcomflot'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.
PAO Sovcomflot Beneish M-Score Chart
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PAO Sovcomflot Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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- |
-2.58 |
-3.42 |
-2.93 |
-2.08 |
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PAO Sovcomflot Quarterly Data
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Jun17 |
Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Jun23 |
| Beneish M-Score |
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-0.82 |
-1.85 |
-2.37 |
-2.08 |
-1.70 |
Competitive Comparison of PAO Sovcomflot's Beneish M-Score
For the Oil & Gas Midstream subindustry, PAO Sovcomflot'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.
PAO Sovcomflot's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, PAO Sovcomflot's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where PAO Sovcomflot's Beneish M-Score falls into.
PAO Sovcomflot 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 PAO Sovcomflot 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 * 1.9303 | + | 0.528 * 0.8402 | + | 0.404 * 0.8715 | + | 0.892 * 1.1843 | + | 0.115 * 0.1106 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.874 | + | 4.679 * -0.030829 | - | 0.327 * 0.6436 |
| = | -1.70 |
* 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 (Jun23) TTM: | Last Year (Mar21) TTM: |
Total Receivables was ₽19,920 Mil.
Revenue was 47733.34 + 28124.873 + 29240.451 + 29178.294 = ₽134,277 Mil.
Gross Profit was 35802.805 + -14985.737 + 13172.379 + 14703.593 = ₽48,693 Mil.
Total Current Assets was ₽115,320 Mil.
Total Assets was ₽551,592 Mil.
Property, Plant and Equipment(Net PPE) was ₽419,761 Mil.
Depreciation, Depletion and Amortization(DDA) was ₽898 Mil.
Selling, General, & Admin. Expense(SGA) was ₽6,099 Mil.
Total Current Liabilities was ₽71,552 Mil.
Long-Term Debt & Capital Lease Obligation was ₽91,260 Mil.
Net Income was 16524.865 + 1200.852 + 1151.832 + 857.057 = ₽19,735 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₽0 Mil.
Cash Flow from Operations was 0 + 11207.585 + 13162.295 + 12369.547 = ₽36,739 Mil.
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Total Receivables was ₽8,714 Mil.
Revenue was 27542.222 + 26397.035 + 27398.127 + 32048.054 = ₽113,385 Mil.
Gross Profit was 14404.681 + -15967.979 + 14643.289 + 21464.918 = ₽34,545 Mil.
Total Current Assets was ₽77,467 Mil.
Total Assets was ₽587,825 Mil.
Property, Plant and Equipment(Net PPE) was ₽490,170 Mil.
Depreciation, Depletion and Amortization(DDA) was ₽116 Mil.
Selling, General, & Admin. Expense(SGA) was ₽5,892 Mil.
Total Current Liabilities was ₽43,174 Mil.
Long-Term Debt & Capital Lease Obligation was ₽226,426 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) |
| = | (19919.583 / 134276.958) | / | (8713.627 / 113385.438) |
| = | 0.148347 | / | 0.07685 |
| | = | 1.9303 |
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) |
| = | (34544.909 / 113385.438) | / | (48693.04 / 134276.958) |
| = | 0.304668 | / | 0.362631 |
| | = | 0.8402 |
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 - (115319.874 + 419761.476) / 551592.012) | / | (1 - (77466.863 + 490169.658) / 587825.238) |
| = | 0.029933 | / | 0.034345 |
| | = | 0.8715 |
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 |
| = | 134276.958 | / | 113385.438 |
| | = | 1.1843 |
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)) |
| = | (115.565 / (115.565 + 490169.658)) | / | (897.833 / (897.833 + 419761.476)) |
| = | 0.000236 | / | 0.002134 |
| | = | 0.1106 |
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) |
| = | (6098.918 / 134276.958) | / | (5892.038 / 113385.438) |
| = | 0.04542 | / | 0.051965 |
| | = | 0.874 |
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) |
| = | ((91260.371 + 71552.044) / 551592.012) | / | ((226425.728 + 43173.739) / 587825.238) |
| = | 0.295168 | / | 0.458639 |
| | = | 0.6436 |
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 |
| = | (19734.606 - 0 | - | 36739.427) | / | 551592.012 |
| | = | -0.030829 |
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.
PAO Sovcomflot has a M-score of -1.70 signals that the company is likely to be a manipulator.
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