MOSENERGO Beneish M-Score Historical Data
The historical data trend for MOSENERGO'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.
MOSENERGO Beneish M-Score Chart
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MOSENERGO Annual Data
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Trend |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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-2.54 |
-2.58 |
-2.44 |
-2.70 |
-2.57 |
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MOSENERGO Quarterly Data
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Jun18 |
Sep18 |
Dec18 |
Mar19 |
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Sep19 |
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Mar20 |
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Sep20 |
Dec20 |
Mar21 |
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Mar22 |
Jun22 |
Sep22 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.57 |
-2.48 |
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-2.53 |
-2.99 |
Competitive Comparison of MOSENERGO's Beneish M-Score
For the Utilities - Independent Power Producers subindustry, MOSENERGO'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.
MOSENERGO's Beneish M-Score Distribution in the Utilities - Independent Power Producers Industry
For the Utilities - Independent Power Producers industry and Utilities sector, MOSENERGO's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where MOSENERGO's Beneish M-Score falls into.
MOSENERGO 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 MOSENERGO 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 * 0.9724 | + | 0.528 * 1.0196 | + | 0.404 * 0.9851 | + | 0.892 * 0.7254 | + | 0.115 * 1.1436 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1704 | + | 4.679 * -0.088647 | - | 0.327 * 0.4504 |
| = | -2.99 |
* 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 (Sep23) TTM: | Last Year (Mar22) TTM: |
Total Receivables was ₽60,268 Mil.
Revenue was 39198 + 43193 + 36270 + 42604 = ₽161,265 Mil.
Gross Profit was 36448 + 40509 + 33709 + 40198 = ₽150,864 Mil.
Total Current Assets was ₽84,279 Mil.
Total Assets was ₽460,996 Mil.
Property, Plant and Equipment(Net PPE) was ₽331,954 Mil.
Depreciation, Depletion and Amortization(DDA) was ₽27,130 Mil.
Selling, General, & Admin. Expense(SGA) was ₽1,986 Mil.
Total Current Liabilities was ₽15,229 Mil.
Long-Term Debt & Capital Lease Obligation was ₽3,579 Mil.
Net Income was -4834 + -934 + -1290 + -766 = ₽-7,824 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₽0 Mil.
Cash Flow from Operations was 10265 + 0 + 16960 + 5817 = ₽33,042 Mil.
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Total Receivables was ₽85,438 Mil.
Revenue was 75173 + 69841 + 37665 + 39620 = ₽222,299 Mil.
Gross Profit was 73378 + 66416 + 34887 + 37349 = ₽212,030 Mil.
Total Current Assets was ₽101,341 Mil.
Total Assets was ₽393,130 Mil.
Property, Plant and Equipment(Net PPE) was ₽253,039 Mil.
Depreciation, Depletion and Amortization(DDA) was ₽23,932 Mil.
Selling, General, & Admin. Expense(SGA) was ₽2,339 Mil.
Total Current Liabilities was ₽30,223 Mil.
Long-Term Debt & Capital Lease Obligation was ₽5,391 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) |
| = | (60268 / 161265) | / | (85438 / 222299) |
| = | 0.37372 | / | 0.384338 |
| | = | 0.9724 |
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) |
| = | (212030 / 222299) | / | (150864 / 161265) |
| = | 0.953805 | / | 0.935504 |
| | = | 1.0196 |
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 - (84279 + 331954) / 460996) | / | (1 - (101341 + 253039) / 393130) |
| = | 0.097101 | / | 0.098568 |
| | = | 0.9851 |
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 |
| = | 161265 | / | 222299 |
| | = | 0.7254 |
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)) |
| = | (23932 / (23932 + 253039)) | / | (27130 / (27130 + 331954)) |
| = | 0.086406 | / | 0.075553 |
| | = | 1.1436 |
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) |
| = | (1986 / 161265) | / | (2339 / 222299) |
| = | 0.012315 | / | 0.010522 |
| | = | 1.1704 |
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) |
| = | ((3579 + 15229) / 460996) | / | ((5391 + 30223) / 393130) |
| = | 0.040799 | / | 0.090591 |
| | = | 0.4504 |
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 |
| = | (-7824 - 0 | - | 33042) | / | 460996 |
| | = | -0.088647 |
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.
MOSENERGO has a M-score of -2.99 suggests that the company is unlikely to be a manipulator.
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