Magnera Beneish M-Score Historical Data
The historical data trend for Magnera'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.
Magnera Beneish M-Score Chart
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Magnera Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.65 |
-2.74 |
-2.29 |
-2.17 |
-2.61 |
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Magnera Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.61 |
-2.63 |
-2.82 |
-2.70 |
-1.06 |
Competitive Comparison of Magnera's Beneish M-Score
For the Paper & Paper Products subindustry, Magnera'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.
Magnera's Beneish M-Score Distribution in the Forest Products Industry
For the Forest Products industry and Basic Materials sector, Magnera's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Magnera's Beneish M-Score falls into.
Magnera 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 Magnera 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 * 2.2766 | + | 0.528 * 0.8904 | + | 0.404 * 1.6294 | + | 0.892 * 1.2203 | + | 0.115 * 1.3725 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0602 | + | 4.679 * 0.002366 | - | 0.327 * 1.582 |
| = | -1.06 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was $475 Mil.
Revenue was 702 + 332.101 + 329.443 + 327.256 = $1,691 Mil.
Gross Profit was 71 + 35.481 + 36.787 + 34.51 = $178 Mil.
Total Current Assets was $1,338 Mil.
Total Assets was $3,993 Mil.
Property, Plant and Equipment(Net PPE) was $1,532 Mil.
Depreciation, Depletion and Amortization(DDA) was $100 Mil.
Selling, General, & Admin. Expense(SGA) was $142 Mil.
Total Current Liabilities was $2,534 Mil.
Long-Term Debt & Capital Lease Obligation was $2,045 Mil.
Net Income was -60 + -15.247 + -16.279 + -26.347 = $-118 Mil.
Non Operating Income was -53 + -3.315 + -2.582 + -2.025 = $-61 Mil.
Cash Flow from Operations was -58 + 12.155 + 12.933 + -33.485 = $-66 Mil.
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Total Receivables was $171 Mil.
Revenue was 320.382 + 329.921 + 357.005 + 378.208 = $1,386 Mil.
Gross Profit was 30.873 + 44.487 + 18.133 + 36.214 = $130 Mil.
Total Current Assets was $606 Mil.
Total Assets was $1,564 Mil.
Property, Plant and Equipment(Net PPE) was $688 Mil.
Depreciation, Depletion and Amortization(DDA) was $63 Mil.
Selling, General, & Admin. Expense(SGA) was $110 Mil.
Total Current Liabilities was $280 Mil.
Long-Term Debt & Capital Lease Obligation was $853 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) |
| = | (475 / 1690.8) | / | (170.974 / 1385.516) |
| = | 0.280932 | / | 0.123401 |
| | = | 2.2766 |
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) |
| = | (129.707 / 1385.516) | / | (177.778 / 1690.8) |
| = | 0.093616 | / | 0.105144 |
| | = | 0.8904 |
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 - (1338 + 1532) / 3993) | / | (1 - (605.967 + 687.907) / 1563.796) |
| = | 0.281242 | / | 0.172607 |
| | = | 1.6294 |
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 |
| = | 1690.8 | / | 1385.516 |
| | = | 1.2203 |
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)) |
| = | (63.247 / (63.247 + 687.907)) | / | (100.125 / (100.125 + 1532)) |
| = | 0.0842 | / | 0.061346 |
| | = | 1.3725 |
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) |
| = | (141.988 / 1690.8) | / | (109.741 / 1385.516) |
| = | 0.083977 | / | 0.079206 |
| | = | 1.0602 |
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) |
| = | ((2045 + 2534) / 3993) | / | ((853.163 + 280.368) / 1563.796) |
| = | 1.146757 | / | 0.724859 |
| | = | 1.582 |
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 |
| = | (-117.873 - -60.922 | - | -66.397) | / | 3993 |
| | = | 0.002366 |
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.
Magnera has a M-score of -1.06 signals that the company is likely to be a manipulator.
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