EnerSys Beneish M-Score Historical Data
The historical data trend for EnerSys'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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EnerSys Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.06 |
-2.61 |
-2.67 |
-2.04 |
-2.66 |
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EnerSys 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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- |
-2.66 |
- |
- |
- |
Competitive Comparison
For the Electrical Equipment & Parts subindustry, EnerSys'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.
EnerSys Beneish M-Score Distribution
For the Industrial Products industry and Industrials sector, EnerSys's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where EnerSys's Beneish M-Score falls into.
EnerSys 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 EnerSys 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 * 0.7886 | + | 0.528 * 0.9861 | + | 0.404 * 1.0059 | + | 0.892 * 1.1046 | + | 0.115 * 1.0611 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.021848 | - | 0.327 * 0.928 |
| = | -2.66 |
* 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 (Mar23) TTM: | Last Year (Mar22) TTM: |
Total Receivables was $693 Mil.
Revenue was $3,709 Mil.
Gross Profit was $840 Mil.
Total Current Assets was $1,896 Mil.
Total Assets was $3,617 Mil.
Property, Plant and Equipment(Net PPE) was $513 Mil.
Depreciation, Depletion and Amortization(DDA) was $91 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $718 Mil.
Long-Term Debt & Capital Lease Obligation was $1,109 Mil.
Net Income was $176 Mil.
Gross Profit was $-25 Mil.
Cash Flow from Operations was $280 Mil.
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Total Receivables was $796 Mil.
Revenue was $3,357 Mil.
Gross Profit was $750 Mil.
Total Current Assets was $1,993 Mil.
Total Assets was $3,737 Mil.
Property, Plant and Equipment(Net PPE) was $503 Mil.
Depreciation, Depletion and Amortization(DDA) was $96 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $738 Mil.
Long-Term Debt & Capital Lease Obligation was $1,296 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) |
| = | (693.411 / 3708.579) | / | (796.028 / 3357.319) |
| = | 0.186975 | / | 0.237102 |
| | = | 0.7886 |
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) |
| = | (749.968 / 3357.319) | / | (840.138 / 3708.579) |
| = | 0.223383 | / | 0.226539 |
| | = | 0.9861 |
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 - (1895.881 + 513.283) / 3616.674) | / | (1 - (1993.193 + 503.264) / 3736.646) |
| = | 0.333873 | / | 0.331899 |
| | = | 1.0059 |
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 |
| = | 3708.579 | / | 3357.319 |
| | = | 1.1046 |
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)) |
| = | (95.878 / (95.878 + 503.264)) | / | (91.153 / (91.153 + 513.283)) |
| = | 0.160026 | / | 0.150807 |
| | = | 1.0611 |
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 / 3708.579) | / | (0 / 3357.319) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((1108.798 + 718.32) / 3616.674) | / | ((1296.137 + 738.13) / 3736.646) |
| = | 0.505193 | / | 0.54441 |
| | = | 0.928 |
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 |
| = | (175.81 - -25.112 | - | 279.938) | / | 3616.674 |
| | = | -0.021848 |
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.
EnerSys has a M-score of -2.66 suggests that the company is unlikely to be a manipulator.
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