FirstEnergy Beneish M-Score Historical Data
The historical data trend for FirstEnergy'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.
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FirstEnergy Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.81 |
-2.49 |
-2.48 |
-2.31 |
-2.20 |
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FirstEnergy 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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-2.31 |
-2.38 |
-2.39 |
-2.36 |
-2.20 |
Competitive Comparison
For the Utilities - Regulated Electric subindustry, FirstEnergy'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.
FirstEnergy Beneish M-Score Distribution
For the Utilities - Regulated industry and Utilities sector, FirstEnergy's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where FirstEnergy's Beneish M-Score falls into.
FirstEnergy 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 FirstEnergy 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 * 0.9761 | + | 0.528 * 0.988 | + | 0.404 * 0.9939 | + | 0.892 * 1.033 | + | 0.115 * 1.0861 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * -1.0488 | + | 4.679 * -0.012057 | - | 0.327 * 1.0623 |
| = | -2.20 |
* 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 $1,584 Mil.
Revenue was 3146 + 3487 + 3006 + 3231 = $12,870 Mil.
Gross Profit was 2112 + 2166 + 1972 + 1974 = $8,224 Mil.
Total Current Assets was $2,568 Mil.
Total Assets was $48,767 Mil.
Property, Plant and Equipment(Net PPE) was $38,412 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,280 Mil.
Selling, General, & Admin. Expense(SGA) was $78 Mil.
Total Current Liabilities was $5,386 Mil.
Long-Term Debt & Capital Lease Obligation was $22,885 Mil.
Net Income was 175 + 400 + 235 + 292 = $1,102 Mil.
Non Operating Income was 103 + 67 + 42 + 91 = $303 Mil.
Cash Flow from Operations was 958 + 642 + -101 + -112 = $1,387 Mil.
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Total Receivables was $1,571 Mil.
Revenue was 3177 + 3475 + 2818 + 2989 = $12,459 Mil.
Gross Profit was 1909 + 2157 + 1826 + 1974 = $7,866 Mil.
Total Current Assets was $2,415 Mil.
Total Assets was $46,108 Mil.
Property, Plant and Equipment(Net PPE) was $36,285 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,317 Mil.
Selling, General, & Admin. Expense(SGA) was $-72 Mil.
Total Current Liabilities was $3,958 Mil.
Long-Term Debt & Capital Lease Obligation was $21,203 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) |
| = | (1584 / 12870) | / | (1571 / 12459) |
| = | 0.123077 | / | 0.126094 |
| | = | 0.9761 |
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) |
| = | (7866 / 12459) | / | (8224 / 12870) |
| = | 0.631351 | / | 0.639005 |
| | = | 0.988 |
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 - (2568 + 38412) / 48767) | / | (1 - (2415 + 36285) / 46108) |
| = | 0.159678 | / | 0.160666 |
| | = | 0.9939 |
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 |
| = | 12870 | / | 12459 |
| | = | 1.033 |
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)) |
| = | (1317 / (1317 + 36285)) | / | (1280 / (1280 + 38412)) |
| = | 0.035025 | / | 0.032248 |
| | = | 1.0861 |
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) |
| = | (78 / 12870) | / | (-72 / 12459) |
| = | 0.006061 | / | -0.005779 |
| | = | -1.0488 |
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) |
| = | ((22885 + 5386) / 48767) | / | ((21203 + 3958) / 46108) |
| = | 0.579716 | / | 0.545697 |
| | = | 1.0623 |
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 |
| = | (1102 - 303 | - | 1387) | / | 48767 |
| | = | -0.012057 |
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.
FirstEnergy has a M-score of -2.20 suggests that the company is unlikely to be a manipulator.
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