Basf SE Beneish M-Score Historical Data
The historical data trend for Basf SE'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.
Basf SE Beneish M-Score Chart
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Basf SE Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.25 |
-2.80 |
-2.26 |
-3.00 |
-3.15 |
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Basf SE Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.99 |
-3.26 |
-3.40 |
-3.15 |
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Competitive Comparison of Basf SE's Beneish M-Score
For the Chemicals subindustry, Basf SE'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.
Basf SE's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Basf SE's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Basf SE's Beneish M-Score falls into.
Basf SE 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 Basf SE 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 * 1.0847 | + | 0.528 * 0.9782 | + | 0.404 * 0.9756 | + | 0.892 * 0.8184 | + | 0.115 * 0.9103 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1586 | + | 4.679 * -0.10452 | - | 0.327 * 1.0304 |
| = | -3.12 |
* 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 $19,270 Mil.
Revenue was 19079.348 + 17307.525 + 16792.956 + 18748.646 = $71,928 Mil.
Gross Profit was 5379.348 + 4039.258 + 3850.587 + 4488.624 = $17,758 Mil.
Total Current Assets was $37,868 Mil.
Total Assets was $88,848 Mil.
Property, Plant and Equipment(Net PPE) was $26,714 Mil.
Depreciation, Depletion and Amortization(DDA) was $5,380 Mil.
Selling, General, & Admin. Expense(SGA) was $11,027 Mil.
Total Current Liabilities was $18,158 Mil.
Long-Term Debt & Capital Lease Obligation was $20,637 Mil.
Net Income was 1486.957 + -1730.643 + -265.742 + 540.628 = $31 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was -557.609 + 4648.855 + 2866.596 + 2359.697 = $9,318 Mil.
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Total Receivables was $21,707 Mil.
Revenue was 21403.64 + 20470.339 + 21728.713 + 24285.412 = $87,888 Mil.
Gross Profit was 5617.773 + 4598.517 + 4835.644 + 6172.304 = $21,224 Mil.
Total Current Assets was $41,904 Mil.
Total Assets was $92,226 Mil.
Property, Plant and Equipment(Net PPE) was $24,504 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,412 Mil.
Selling, General, & Admin. Expense(SGA) was $11,629 Mil.
Total Current Liabilities was $21,086 Mil.
Long-Term Debt & Capital Lease Obligation was $17,997 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) |
| = | (19269.565 / 71928.475) | / | (21706.638 / 87888.104) |
| = | 0.267899 | / | 0.24698 |
| | = | 1.0847 |
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) |
| = | (21224.238 / 87888.104) | / | (17757.817 / 71928.475) |
| = | 0.241492 | / | 0.246882 |
| | = | 0.9782 |
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 - (37868.478 + 26714.13) / 88847.826) | / | (1 - (41903.64 + 24504.283) / 92225.91) |
| = | 0.27311 | / | 0.279943 |
| | = | 0.9756 |
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 |
| = | 71928.475 | / | 87888.104 |
| | = | 0.8184 |
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)) |
| = | (4412.249 / (4412.249 + 24504.283)) | / | (5379.607 / (5379.607 + 26714.13)) |
| = | 0.152586 | / | 0.167622 |
| | = | 0.9103 |
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) |
| = | (11026.865 / 71928.475) | / | (11628.839 / 87888.104) |
| = | 0.153303 | / | 0.132314 |
| | = | 1.1586 |
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) |
| = | ((20636.957 + 18157.609) / 88847.826) | / | ((17996.788 + 21085.653) / 92225.91) |
| = | 0.436641 | / | 0.423769 |
| | = | 1.0304 |
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 |
| = | (31.2 - 0 | - | 9317.539) | / | 88847.826 |
| | = | -0.10452 |
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.
Basf SE has a M-score of -3.12 suggests that the company is unlikely to be a manipulator.
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