Arkema Beneish M-Score Historical Data
The historical data trend for Arkema'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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Arkema Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.82 |
-2.85 |
-2.11 |
-2.56 |
-2.80 |
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Arkema 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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-2.56 |
-2.74 |
-2.86 |
-2.88 |
-2.80 |
Competitive Comparison
For the Specialty Chemicals subindustry, Arkema'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.
Arkema Beneish M-Score Distribution
For the Chemicals industry and Basic Materials sector, Arkema's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Arkema's Beneish M-Score falls into.
Arkema 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 Arkema 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 * 1.124 | + | 0.528 * 1.0874 | + | 0.404 * 1.0372 | + | 0.892 * 0.8444 | + | 0.115 * 1.0624 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2217 | + | 4.679 * -0.058349 | - | 0.327 * 1.0886 |
| = | -2.78 |
* 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 $1,455 Mil.
Revenue was 2423.119 + 2482.391 + 2645.72 + 2702.355 = $10,254 Mil.
Gross Profit was 463.468 + 524.013 + 587.216 + 537.473 = $2,112 Mil.
Total Current Assets was $5,298 Mil.
Total Assets was $15,831 Mil.
Property, Plant and Equipment(Net PPE) was $4,068 Mil.
Depreciation, Depletion and Amortization(DDA) was $774 Mil.
Selling, General, & Admin. Expense(SGA) was $942 Mil.
Total Current Liabilities was $2,267 Mil.
Long-Term Debt & Capital Lease Obligation was $4,072 Mil.
Net Income was 21.81 + 121.665 + 164.68 + 141.328 = $449 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 503.817 + 419.424 + 296.858 + 153.105 = $1,373 Mil.
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Total Receivables was $1,533 Mil.
Revenue was 2655.72 + 2942.574 + 3365.751 + 3179.515 = $12,144 Mil.
Gross Profit was 400.424 + 609.901 + 881.607 + 828.194 = $2,720 Mil.
Total Current Assets was $5,044 Mil.
Total Assets was $14,313 Mil.
Property, Plant and Equipment(Net PPE) was $3,632 Mil.
Depreciation, Depletion and Amortization(DDA) was $744 Mil.
Selling, General, & Admin. Expense(SGA) was $913 Mil.
Total Current Liabilities was $2,553 Mil.
Long-Term Debt & Capital Lease Obligation was $2,712 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) |
| = | (1454.744 / 10253.585) | / | (1532.839 / 12143.56) |
| = | 0.141877 | / | 0.126226 |
| | = | 1.124 |
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) |
| = | (2720.126 / 12143.56) | / | (2112.17 / 10253.585) |
| = | 0.223997 | / | 0.205993 |
| | = | 1.0874 |
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 - (5297.71 + 4067.612) / 15830.971) | / | (1 - (5044.492 + 3632.415) / 14312.5) |
| = | 0.408418 | / | 0.393753 |
| | = | 1.0372 |
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 |
| = | 10253.585 | / | 12143.56 |
| | = | 0.8444 |
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)) |
| = | (743.532 / (743.532 + 3632.415)) | / | (774.385 / (774.385 + 4067.612)) |
| = | 0.169913 | / | 0.159931 |
| | = | 1.0624 |
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) |
| = | (942.116 / 10253.585) | / | (913.304 / 12143.56) |
| = | 0.091882 | / | 0.075209 |
| | = | 1.2217 |
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) |
| = | ((4071.974 + 2267.176) / 15830.971) | / | ((2711.864 + 2552.966) / 14312.5) |
| = | 0.400427 | / | 0.367848 |
| | = | 1.0886 |
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 |
| = | (449.483 - 0 | - | 1373.204) | / | 15830.971 |
| | = | -0.058349 |
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.
Arkema has a M-score of -2.78 suggests that the company is unlikely to be a manipulator.
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