Energa Beneish M-Score Historical Data
The historical data trend for Energa'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.
Energa Beneish M-Score Chart
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Energa Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.57 |
-3.49 |
-2.67 |
-2.15 |
-2.47 |
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Energa Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.15 |
-1.84 |
-1.85 |
-2.19 |
-2.47 |
Competitive Comparison of Energa's Beneish M-Score
For the Utilities - Regulated Electric subindustry, Energa'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.
Energa's Beneish M-Score Distribution in the Utilities - Regulated Industry
For the Utilities - Regulated industry and Utilities sector, Energa's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Energa's Beneish M-Score falls into.
Energa 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 Energa 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 * 1.2228 | + | 0.528 * 0.8018 | + | 0.404 * 0.5472 | + | 0.892 * 1.276 | + | 0.115 * 1.084 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4425 | + | 4.679 * -0.013069 | - | 0.327 * 1.0764 |
| = | -2.47 |
* 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 zł5,143 Mil.
Revenue was 6598 + 6055 + 6011 + 7423 = zł26,087 Mil.
Gross Profit was 3 + 932 + 469 + 2807 = zł4,211 Mil.
Total Current Assets was zł8,350 Mil.
Total Assets was zł31,679 Mil.
Property, Plant and Equipment(Net PPE) was zł21,843 Mil.
Depreciation, Depletion and Amortization(DDA) was zł1,194 Mil.
Selling, General, & Admin. Expense(SGA) was zł2,540 Mil.
Total Current Liabilities was zł12,939 Mil.
Long-Term Debt & Capital Lease Obligation was zł4,257 Mil.
Net Income was -1013 + 206 + -133 + 1557 = zł617 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = zł0 Mil.
Cash Flow from Operations was -693 + 1222 + 1038 + -536 = zł1,031 Mil.
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Total Receivables was zł3,296 Mil.
Revenue was 5420 + 5507 + 4579 + 4938 = zł20,444 Mil.
Gross Profit was -546 + 1047 + 1001 + 1144 = zł2,646 Mil.
Total Current Assets was zł5,862 Mil.
Total Assets was zł27,248 Mil.
Property, Plant and Equipment(Net PPE) was zł19,050 Mil.
Depreciation, Depletion and Amortization(DDA) was zł1,134 Mil.
Selling, General, & Admin. Expense(SGA) was zł1,380 Mil.
Total Current Liabilities was zł9,428 Mil.
Long-Term Debt & Capital Lease Obligation was zł4,313 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) |
| = | (5143 / 26087) | / | (3296 / 20444) |
| = | 0.197148 | / | 0.161221 |
| | = | 1.2228 |
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) |
| = | (2646 / 20444) | / | (4211 / 26087) |
| = | 0.129427 | / | 0.161421 |
| | = | 0.8018 |
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 - (8350 + 21843) / 31679) | / | (1 - (5862 + 19050) / 27248) |
| = | 0.046908 | / | 0.085731 |
| | = | 0.5472 |
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 |
| = | 26087 | / | 20444 |
| | = | 1.276 |
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)) |
| = | (1134 / (1134 + 19050)) | / | (1194 / (1194 + 21843)) |
| = | 0.056183 | / | 0.05183 |
| | = | 1.084 |
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) |
| = | (2540 / 26087) | / | (1380 / 20444) |
| = | 0.097367 | / | 0.067501 |
| | = | 1.4425 |
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) |
| = | ((4257 + 12939) / 31679) | / | ((4313 + 9428) / 27248) |
| = | 0.54282 | / | 0.504294 |
| | = | 1.0764 |
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 |
| = | (617 - 0 | - | 1031) | / | 31679 |
| | = | -0.013069 |
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.
Energa has a M-score of -2.47 suggests that the company is unlikely to be a manipulator.
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