Suzano Beneish M-Score Historical Data
The historical data trend for Suzano'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.
Suzano Beneish M-Score Chart
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Suzano Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-0.75 |
-2.89 |
-2.01 |
-2.41 |
-2.99 |
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Suzano 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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-2.41 |
-1.82 |
-2.69 |
-2.94 |
-2.99 |
Competitive Comparison of Suzano's Beneish M-Score
For the Paper & Paper Products subindustry, Suzano'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.
Suzano's Beneish M-Score Distribution in the Forest Products Industry
For the Forest Products industry and Basic Materials sector, Suzano's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Suzano's Beneish M-Score falls into.
Suzano 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 Suzano 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 * 0.9541 | + | 0.528 * 1.3593 | + | 0.404 * 0.9329 | + | 0.892 * 0.7978 | + | 0.115 * 1.1543 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2708 | + | 4.679 * -0.093921 | - | 0.327 * 0.9424 |
| = | -2.99 |
* 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 R$7,737 Mil.
Revenue was 10371.545 + 8948.013 + 9159.634 + 11276.383 = R$39,756 Mil.
Gross Profit was 3595.981 + 2843.757 + 2931.453 + 5307.709 = R$14,679 Mil.
Total Current Assets was R$38,569 Mil.
Total Assets was R$143,593 Mil.
Property, Plant and Equipment(Net PPE) was R$64,486 Mil.
Depreciation, Depletion and Amortization(DDA) was R$7,321 Mil.
Selling, General, & Admin. Expense(SGA) was R$3,983 Mil.
Total Current Liabilities was R$14,795 Mil.
Long-Term Debt & Capital Lease Obligation was R$77,905 Mil.
Net Income was 4507.343 + -732.993 + 5073.127 + 5237.371 = R$14,085 Mil.
Non Operating Income was 4503.632 + -2750.703 + 5266.531 + 3236.353 = R$10,256 Mil.
Cash Flow from Operations was 4561.707 + 2485.726 + 5970.835 + 4297.21 = R$17,315 Mil.
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Total Receivables was R$10,164 Mil.
Revenue was 14369.707 + 14198.749 + 11519.655 + 9742.835 = R$49,831 Mil.
Gross Profit was 7576.854 + 7726.079 + 5396.73 + 4309.995 = R$25,010 Mil.
Total Current Assets was R$37,123 Mil.
Total Assets was R$133,198 Mil.
Property, Plant and Equipment(Net PPE) was R$55,766 Mil.
Depreciation, Depletion and Amortization(DDA) was R$7,438 Mil.
Selling, General, & Admin. Expense(SGA) was R$3,929 Mil.
Total Current Liabilities was R$14,493 Mil.
Long-Term Debt & Capital Lease Obligation was R$76,750 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) |
| = | (7736.993 / 39755.575) | / | (10163.926 / 49830.946) |
| = | 0.194614 | / | 0.203968 |
| | = | 0.9541 |
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) |
| = | (25009.658 / 49830.946) | / | (14678.9 / 39755.575) |
| = | 0.50189 | / | 0.369229 |
| | = | 1.3593 |
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 - (38569.072 + 64485.7) / 143593.025) | / | (1 - (37122.65 + 55765.86) / 133197.968) |
| = | 0.282314 | / | 0.302628 |
| | = | 0.9329 |
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 |
| = | 39755.575 | / | 49830.946 |
| | = | 0.7978 |
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)) |
| = | (7438.091 / (7438.091 + 55765.86)) | / | (7321.11 / (7321.11 + 64485.7)) |
| = | 0.117684 | / | 0.101956 |
| | = | 1.1543 |
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) |
| = | (3983.223 / 39755.575) | / | (3928.777 / 49830.946) |
| = | 0.100193 | / | 0.078842 |
| | = | 1.2708 |
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) |
| = | ((77904.828 + 14795.04) / 143593.025) | / | ((76749.918 + 14492.543) / 133197.968) |
| = | 0.645574 | / | 0.685014 |
| | = | 0.9424 |
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 |
| = | (14084.848 - 10255.813 | - | 17315.478) | / | 143593.025 |
| | = | -0.093921 |
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.
Suzano has a M-score of -2.99 suggests that the company is unlikely to be a manipulator.
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