Transneft PJSC Beneish M-Score Historical Data
The historical data trend for Transneft PJSC'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.
Transneft PJSC Beneish M-Score Chart
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Transneft PJSC Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.32 |
-2.93 |
-2.87 |
-2.43 |
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Transneft PJSC Quarterly Data
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Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Jun22 |
Sep22 |
Dec22 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.43 |
-2.00 |
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Competitive Comparison of Transneft PJSC's Beneish M-Score
For the Oil & Gas Midstream subindustry, Transneft PJSC'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.
Transneft PJSC's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Transneft PJSC's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Transneft PJSC's Beneish M-Score falls into.
Transneft PJSC 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 Transneft PJSC 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 (Dec23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was ₽64,478 Mil.
Revenue was 350785 + 343433 + 322505 + 295507 = ₽1,312,230 Mil.
Gross Profit was 167233 + 163795 + 180066 + 150759 = ₽661,853 Mil.
Total Current Assets was ₽810,369 Mil.
Total Assets was ₽3,654,474 Mil.
Property, Plant and Equipment(Net PPE) was ₽2,641,015 Mil.
Depreciation, Depletion and Amortization(DDA) was ₽0 Mil.
Selling, General, & Admin. Expense(SGA) was ₽0 Mil.
Total Current Liabilities was ₽334,684 Mil.
Long-Term Debt & Capital Lease Obligation was ₽275,328 Mil.
Net Income was 51177 + 63819 + 93018 + 75267 = ₽283,281 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₽0 Mil.
Cash Flow from Operations was 198706 + 90125 + 0 + 166299 = ₽455,130 Mil.
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Total Receivables was ₽0 Mil.
Revenue was 293215 + 303532 + 276303 + 276014 = ₽1,149,064 Mil.
Gross Profit was 152660 + 164519 + 158309 + 162675 = ₽638,163 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 ₽0 Mil.
Selling, General, & Admin. Expense(SGA) was ₽23,768 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) |
| = | (64478 / 1312230) | / | (0 / 1149064) |
| = | 0.049136 | / | 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) |
| = | (638163 / 1149064) | / | (661853 / 1312230) |
| = | 0.555376 | / | 0.504373 |
| | = | |
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 - (810369 + 2641015) / 3654474) | / | (1 - (0 + 0) / 0) |
| = | 0.055573 | / | |
| | = | |
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 |
| = | 1312230 | / | 1149064 |
| | = | |
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 + 0)) | / | (0 / (0 + 2641015)) |
| = | | / | 0 |
| | = | |
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) |
| = | (0 / 1312230) | / | (23768 / 1149064) |
| = | 0 | / | 0.020685 |
| | = | |
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) |
| = | ((275328 + 334684) / 3654474) | / | ((0 + 0) / 0) |
| = | 0.166922 | / | |
| | = | |
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 |
| = | (283281 - 0 | - | 455130) | / | 3654474 |
| | = | -0.047024 |
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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