Calumet Beneish M-Score Historical Data
The historical data trend for Calumet'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.
Calumet Beneish M-Score Chart
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Calumet Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.10 |
-2.38 |
-2.83 |
-2.46 |
-2.36 |
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Calumet Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.46 |
-2.17 |
-2.48 |
-2.03 |
-2.36 |
Competitive Comparison of Calumet's Beneish M-Score
For the Specialty Chemicals subindustry, Calumet'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.
Calumet's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Calumet's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Calumet's Beneish M-Score falls into.
Calumet 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 Calumet 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 * 0.9697 | + | 0.528 * 1.961 | + | 0.404 * 0.9301 | + | 0.892 * 1.002 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0686 | + | 4.679 * -0.065623 | - | 0.327 * 1.0407 |
| = | -2.36 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was $278 Mil.
Revenue was 949.5 + 1100.4 + 1133.7 + 1005.8 = $4,189 Mil.
Gross Profit was 83.6 + 4.9 + 63.8 + 78.5 = $231 Mil.
Total Current Assets was $766 Mil.
Total Assets was $2,758 Mil.
Property, Plant and Equipment(Net PPE) was $1,679 Mil.
Depreciation, Depletion and Amortization(DDA) was $0 Mil.
Selling, General, & Admin. Expense(SGA) was $201 Mil.
Total Current Liabilities was $864 Mil.
Long-Term Debt & Capital Lease Obligation was $2,247 Mil.
Net Income was -40.7 + -100.6 + -39.1 + -41.6 = $-222 Mil.
Non Operating Income was -4.6 + 14.9 + 12 + -16.9 = $5 Mil.
Cash Flow from Operations was -3.4 + -15.5 + 66.5 + -94 = $-46 Mil.
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Total Receivables was $286 Mil.
Revenue was 976.5 + 1149.4 + 1017.8 + 1037.3 = $4,181 Mil.
Gross Profit was 22.1 + 261.5 + 71.5 + 96.6 = $452 Mil.
Total Current Assets was $795 Mil.
Total Assets was $2,751 Mil.
Property, Plant and Equipment(Net PPE) was $1,621 Mil.
Depreciation, Depletion and Amortization(DDA) was $0 Mil.
Selling, General, & Admin. Expense(SGA) was $188 Mil.
Total Current Liabilities was $1,113 Mil.
Long-Term Debt & Capital Lease Obligation was $1,869 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) |
| = | (278.1 / 4189.4) | / | (286.2 / 4181) |
| = | 0.066382 | / | 0.068453 |
| | = | 0.9697 |
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) |
| = | (451.7 / 4181) | / | (230.8 / 4189.4) |
| = | 0.108036 | / | 0.055091 |
| | = | 1.961 |
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 - (766 + 1679) / 2758.2) | / | (1 - (794.7 + 1620.7) / 2751.3) |
| = | 0.113552 | / | 0.122088 |
| | = | 0.9301 |
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 |
| = | 4189.4 | / | 4181 |
| | = | 1.002 |
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)) |
| = | (0 / (0 + 1620.7)) | / | (0 / (0 + 1679)) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (201.2 / 4189.4) | / | (187.9 / 4181) |
| = | 0.048026 | / | 0.044941 |
| | = | 1.0686 |
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) |
| = | ((2246.9 + 863.6) / 2758.2) | / | ((1868.7 + 1112.7) / 2751.3) |
| = | 1.127728 | / | 1.083633 |
| | = | 1.0407 |
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 |
| = | (-222 - 5.4 | - | -46.4) | / | 2758.2 |
| | = | -0.065623 |
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.
Calumet has a M-score of -2.36 suggests that the company is unlikely to be a manipulator.
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