Alleima AB Beneish M-Score Historical Data
The historical data trend for Alleima AB'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.
Alleima AB Beneish M-Score Chart
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Alleima AB Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-1.84 |
-2.58 |
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Alleima AB Quarterly Data
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Dec19 |
Dec20 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.76 |
-2.58 |
-2.59 |
-2.88 |
-2.65 |
Competitive Comparison of Alleima AB's Beneish M-Score
For the Steel subindustry, Alleima AB'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.
Alleima AB's Beneish M-Score Distribution in the Steel Industry
For the Steel industry and Basic Materials sector, Alleima AB's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Alleima AB's Beneish M-Score falls into.
Alleima AB 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 Alleima AB 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 * 1.0802 | + | 0.528 * 1.089 | + | 0.404 * 0.9887 | + | 0.892 * 0.9727 | + | 0.115 * 1.0201 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0588 | + | 4.679 * -0.038235 | - | 0.327 * 0.9634 |
| = | -2.56 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $353 Mil.
Revenue was 439.73 + 511.014 + 455.275 + 491.148 = $1,897 Mil.
Gross Profit was 84.172 + 127.777 + 69.732 + 105.58 = $387 Mil.
Total Current Assets was $1,258 Mil.
Total Assets was $2,239 Mil.
Property, Plant and Equipment(Net PPE) was $754 Mil.
Depreciation, Depletion and Amortization(DDA) was $88 Mil.
Selling, General, & Admin. Expense(SGA) was $216 Mil.
Total Current Liabilities was $435 Mil.
Long-Term Debt & Capital Lease Obligation was $126 Mil.
Net Income was 23.169 + 60.647 + 4.899 + 39.288 = $128 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 56.604 + 54.448 + 24.973 + 77.601 = $214 Mil.
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Total Receivables was $336 Mil.
Revenue was 416.516 + 523.535 + 513.158 + 497.109 = $1,950 Mil.
Gross Profit was 73.975 + 93.694 + 159.121 + 106.764 = $434 Mil.
Total Current Assets was $1,145 Mil.
Total Assets was $2,058 Mil.
Property, Plant and Equipment(Net PPE) was $702 Mil.
Depreciation, Depletion and Amortization(DDA) was $84 Mil.
Selling, General, & Admin. Expense(SGA) was $210 Mil.
Total Current Liabilities was $453 Mil.
Long-Term Debt & Capital Lease Obligation was $83 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) |
| = | (353.016 / 1897.167) | / | (335.956 / 1950.318) |
| = | 0.186075 | / | 0.172257 |
| | = | 1.0802 |
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) |
| = | (433.554 / 1950.318) | / | (387.261 / 1897.167) |
| = | 0.222299 | / | 0.204126 |
| | = | 1.089 |
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 - (1258.383 + 754.13) / 2239.417) | / | (1 - (1144.901 + 702.313) / 2058.134) |
| = | 0.101323 | / | 0.102481 |
| | = | 0.9887 |
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 |
| = | 1897.167 | / | 1950.318 |
| | = | 0.9727 |
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)) |
| = | (84.233 / (84.233 + 702.313)) | / | (88.459 / (88.459 + 754.13)) |
| = | 0.107092 | / | 0.104985 |
| | = | 1.0201 |
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) |
| = | (216.337 / 1897.167) | / | (210.04 / 1950.318) |
| = | 0.114032 | / | 0.107695 |
| | = | 1.0588 |
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) |
| = | ((126.308 + 435.135) / 2239.417) | / | ((82.906 + 452.692) / 2058.134) |
| = | 0.250709 | / | 0.260235 |
| | = | 0.9634 |
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 |
| = | (128.003 - 0 | - | 213.626) | / | 2239.417 |
| | = | -0.038235 |
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.
Alleima AB has a M-score of -2.56 suggests that the company is unlikely to be a manipulator.
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