Cosan Beneish M-Score Historical Data
The historical data trend for Cosan'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.
Cosan Beneish M-Score Chart
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Cosan Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.10 |
-1.40 |
-2.40 |
-2.29 |
-3.09 |
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Cosan 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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-2.29 |
-2.64 |
-2.83 |
-3.02 |
-3.09 |
Competitive Comparison of Cosan's Beneish M-Score
For the Oil & Gas Refining & Marketing subindustry, Cosan'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.
Cosan's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Cosan's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cosan's Beneish M-Score falls into.
Cosan 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 Cosan 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 * 0.9105 | + | 0.528 * 0.8173 | + | 0.404 * 1.0425 | + | 0.892 * 0.9932 | + | 0.115 * 0.7704 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2006 | + | 4.679 * -0.079294 | - | 0.327 * 1.0402 |
| = | -3.09 |
* 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$5,473 Mil.
Revenue was 9573.144 + 10253.57 + 10010.456 + 9631.327 = R$39,468 Mil.
Gross Profit was 2245.962 + 3298.492 + 2875.337 + 2498.81 = R$10,919 Mil.
Total Current Assets was R$28,610 Mil.
Total Assets was R$139,865 Mil.
Property, Plant and Equipment(Net PPE) was R$22,412 Mil.
Depreciation, Depletion and Amortization(DDA) was R$3,365 Mil.
Selling, General, & Admin. Expense(SGA) was R$3,879 Mil.
Total Current Liabilities was R$16,159 Mil.
Long-Term Debt & Capital Lease Obligation was R$56,565 Mil.
Net Income was 2362.471 + 678.752 + -1042.701 + -904.131 = R$1,094 Mil.
Non Operating Income was 2687.623 + 852.922 + -1884.188 + 252.049 = R$1,908 Mil.
Cash Flow from Operations was 1987.819 + 3364.249 + 3107.359 + 1817.017 = R$10,276 Mil.
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Total Receivables was R$6,052 Mil.
Revenue was 10754.095 + 11507.301 + 9571.087 + 7904.887 = R$39,737 Mil.
Gross Profit was 2167.917 + 2808.458 + 2292.207 + 1715.651 = R$8,984 Mil.
Total Current Assets was R$25,578 Mil.
Total Assets was R$134,485 Mil.
Property, Plant and Equipment(Net PPE) was R$26,961 Mil.
Depreciation, Depletion and Amortization(DDA) was R$3,014 Mil.
Selling, General, & Admin. Expense(SGA) was R$3,253 Mil.
Total Current Liabilities was R$15,798 Mil.
Long-Term Debt & Capital Lease Obligation was R$51,427 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) |
| = | (5472.534 / 39468.497) | / | (6051.588 / 39737.37) |
| = | 0.138656 | / | 0.15229 |
| | = | 0.9105 |
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) |
| = | (8984.233 / 39737.37) | / | (10918.601 / 39468.497) |
| = | 0.22609 | / | 0.276641 |
| | = | 0.8173 |
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 - (28610.189 + 22411.657) / 139865.382) | / | (1 - (25577.934 + 26961.305) / 134484.992) |
| = | 0.635207 | / | 0.60933 |
| | = | 1.0425 |
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 |
| = | 39468.497 | / | 39737.37 |
| | = | 0.9932 |
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)) |
| = | (3014.48 / (3014.48 + 26961.305)) | / | (3364.943 / (3364.943 + 22411.657)) |
| = | 0.100564 | / | 0.130543 |
| | = | 0.7704 |
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) |
| = | (3878.545 / 39468.497) | / | (3252.611 / 39737.37) |
| = | 0.098269 | / | 0.081853 |
| | = | 1.2006 |
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) |
| = | ((56564.987 + 16158.805) / 139865.382) | / | ((51426.64 + 15798.213) / 134484.992) |
| = | 0.519956 | / | 0.499869 |
| | = | 1.0402 |
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 |
| = | (1094.391 - 1908.406 | - | 10276.444) | / | 139865.382 |
| | = | -0.079294 |
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.
Cosan has a M-score of -3.09 suggests that the company is unlikely to be a manipulator.
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