Braskem Beneish M-Score Historical Data
The historical data trend for Braskem'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.
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Braskem Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
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|
|
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-2.21 |
-2.46 |
-1.93 |
-2.65 |
-1.68 |
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Braskem 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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|
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|
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-2.65 |
-1.92 |
-1.37 |
-0.28 |
-1.68 |
Competitive Comparison
For the Chemicals subindustry, Braskem'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.
Braskem Beneish M-Score Distribution
For the Chemicals industry and Basic Materials sector, Braskem's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Braskem's Beneish M-Score falls into.
Braskem 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 Braskem 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 * 1.4563 | + | 0.528 * 2.7948 | + | 0.404 * 0.9757 | + | 0.892 * 0.7513 | + | 0.115 * 0.9575 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2366 | + | 4.679 * -0.039406 | - | 0.327 * 1.036 |
| = | -1.59 |
* 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 $1,149 Mil.
Revenue was 3406.466 + 3376.597 + 3658.24 + 3733.441 = $14,175 Mil.
Gross Profit was 205.723 + 115.213 + 94.567 + 189.11 = $605 Mil.
Total Current Assets was $7,641 Mil.
Total Assets was $18,723 Mil.
Property, Plant and Equipment(Net PPE) was $8,618 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,048 Mil.
Selling, General, & Admin. Expense(SGA) was $882 Mil.
Total Current Liabilities was $4,999 Mil.
Long-Term Debt & Capital Lease Obligation was $11,462 Mil.
Net Income was -321.442 + -489.603 + -158.848 + 35.326 = $-935 Mil.
Non Operating Income was 32.042 + -292.587 + 192.431 + 293.553 = $225 Mil.
Cash Flow from Operations was 206.947 + -498.917 + 407.73 + -537.956 = $-422 Mil.
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Total Receivables was $1,050 Mil.
Revenue was 3620.315 + 4841.521 + 5034.174 + 5371.554 = $18,868 Mil.
Gross Profit was -14.87 + 425.09 + 808.091 + 1030.866 = $2,249 Mil.
Total Current Assets was $6,569 Mil.
Total Assets was $16,786 Mil.
Property, Plant and Equipment(Net PPE) was $7,953 Mil.
Depreciation, Depletion and Amortization(DDA) was $921 Mil.
Selling, General, & Admin. Expense(SGA) was $950 Mil.
Total Current Liabilities was $4,611 Mil.
Long-Term Debt & Capital Lease Obligation was $9,634 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) |
| = | (1148.822 / 14174.744) | / | (1050.063 / 18867.564) |
| = | 0.081047 | / | 0.055654 |
| | = | 1.4563 |
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) |
| = | (2249.177 / 18867.564) | / | (604.613 / 14174.744) |
| = | 0.119209 | / | 0.042654 |
| | = | 2.7948 |
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 - (7641.332 + 8618.107) / 18723.417) | / | (1 - (6568.994 + 7952.873) / 16785.946) |
| = | 0.131599 | / | 0.134879 |
| | = | 0.9757 |
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 |
| = | 14174.744 | / | 18867.564 |
| | = | 0.7513 |
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)) |
| = | (921.132 / (921.132 + 7952.873)) | / | (1047.868 / (1047.868 + 8618.107)) |
| = | 0.103801 | / | 0.108408 |
| | = | 0.9575 |
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) |
| = | (882.385 / 14174.744) | / | (949.838 / 18867.564) |
| = | 0.062251 | / | 0.050342 |
| | = | 1.2366 |
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) |
| = | ((11462.305 + 4998.98) / 18723.417) | / | ((9634.156 + 4610.897) / 16785.946) |
| = | 0.879182 | / | 0.84863 |
| | = | 1.036 |
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 |
| = | (-934.567 - 225.439 | - | -422.196) | / | 18723.417 |
| | = | -0.039406 |
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.
Braskem has a M-score of -1.59 signals that the company is likely to be a manipulator.
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