Sylvamo Beneish M-Score Historical Data
The historical data trend for Sylvamo'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.
Sylvamo Beneish M-Score Chart
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Sylvamo Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-2.67 |
-2.68 |
-2.84 |
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Sylvamo Quarterly Data
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Dec18 |
Dec19 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.84 |
-2.61 |
-2.80 |
-2.84 |
-2.81 |
Competitive Comparison of Sylvamo's Beneish M-Score
For the Paper & Paper Products subindustry, Sylvamo'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.
Sylvamo's Beneish M-Score Distribution in the Forest Products Industry
For the Forest Products industry and Basic Materials sector, Sylvamo's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sylvamo's Beneish M-Score falls into.
Sylvamo 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 Sylvamo 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 * 0.9827 | + | 0.528 * 1.2778 | + | 0.404 * 1.0297 | + | 0.892 * 0.9474 | + | 0.115 * 0.9689 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.998 | + | 4.679 * -0.096988 | - | 0.327 * 0.9349 |
| = | -2.82 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was €412 Mil.
Revenue was 832.6 + 883.988 + 840.489 + 848.237 = €3,405 Mil.
Gross Profit was 173.88 + 192.57 + 217.384 + 182.754 = €767 Mil.
Total Current Assets was €1,026 Mil.
Total Assets was €2,573 Mil.
Property, Plant and Equipment(Net PPE) was €966 Mil.
Depreciation, Depletion and Amortization(DDA) was €136 Mil.
Selling, General, & Admin. Expense(SGA) was €309 Mil.
Total Current Liabilities was €597 Mil.
Long-Term Debt & Capital Lease Obligation was €847 Mil.
Net Income was 39.56 + 44.933 + 54.346 + 45.227 = €184 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 24.84 + 153.139 + 184.589 + 71.071 = €434 Mil.
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Total Receivables was €443 Mil.
Revenue was 878.894 + 875.088 + 977.68 + 862.752 = €3,594 Mil.
Gross Profit was 253.114 + 257.712 + 283.81 + 239.338 = €1,034 Mil.
Total Current Assets was €1,129 Mil.
Total Assets was €2,613 Mil.
Property, Plant and Equipment(Net PPE) was €911 Mil.
Depreciation, Depletion and Amortization(DDA) was €124 Mil.
Selling, General, & Admin. Expense(SGA) was €327 Mil.
Total Current Liabilities was €678 Mil.
Long-Term Debt & Capital Lease Obligation was €891 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) |
| = | (412.16 / 3405.314) | / | (442.716 / 3594.414) |
| = | 0.121034 | / | 0.123168 |
| | = | 0.9827 |
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) |
| = | (1033.974 / 3594.414) | / | (766.588 / 3405.314) |
| = | 0.287661 | / | 0.225115 |
| | = | 1.2778 |
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 - (1025.8 + 966) / 2573.24) | / | (1 - (1129.206 + 910.65) / 2613.332) |
| = | 0.225956 | / | 0.219442 |
| | = | 1.0297 |
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 |
| = | 3405.314 | / | 3594.414 |
| | = | 0.9474 |
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)) |
| = | (123.536 / (123.536 + 910.65)) | / | (135.84 / (135.84 + 966)) |
| = | 0.119452 | / | 0.123285 |
| | = | 0.9689 |
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) |
| = | (308.736 / 3405.314) | / | (326.526 / 3594.414) |
| = | 0.090663 | / | 0.090843 |
| | = | 0.998 |
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) |
| = | ((847.32 + 597.08) / 2573.24) | / | ((891.036 + 678.084) / 2613.332) |
| = | 0.561316 | / | 0.600429 |
| | = | 0.9349 |
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 |
| = | (184.066 - 0 | - | 433.639) | / | 2573.24 |
| | = | -0.096988 |
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.
Sylvamo has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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