FMC Beneish M-Score Historical Data
The historical data trend for FMC'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.
FMC Beneish M-Score Chart
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FMC Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.41 |
-2.38 |
-2.27 |
-1.69 |
-2.42 |
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FMC Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-2.06 |
-1.84 |
-1.72 |
-2.42 |
-2.35 |
Competitive Comparison of FMC's Beneish M-Score
For the Agricultural Inputs subindustry, FMC'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.
FMC's Beneish M-Score Distribution in the Agriculture Industry
For the Agriculture industry and Basic Materials sector, FMC's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where FMC's Beneish M-Score falls into.
FMC 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 FMC 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 * 1.0144 | + | 0.528 * 0.9918 | + | 0.404 * 1.0081 | + | 0.892 * 1.0145 | + | 0.115 * 1.0352 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9032 | + | 4.679 * 0.015634 | - | 0.327 * 0.9773 |
| = | -2.35 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $2,900 Mil.
Revenue was 791.4 + 1224.3 + 1065.4 + 1038.4 = $4,120 Mil.
Gross Profit was 316.7 + 524.7 + 386.4 + 398.1 = $1,626 Mil.
Total Current Assets was $5,078 Mil.
Total Assets was $11,801 Mil.
Property, Plant and Equipment(Net PPE) was $859 Mil.
Depreciation, Depletion and Amortization(DDA) was $174 Mil.
Selling, General, & Admin. Expense(SGA) was $653 Mil.
Total Current Liabilities was $3,305 Mil.
Long-Term Debt & Capital Lease Obligation was $3,028 Mil.
Net Income was -15.5 + -16.3 + 65 + 295.1 = $328 Mil.
Non Operating Income was -21 + 8.2 + -27 + -93.6 = $-133 Mil.
Cash Flow from Operations was -558.3 + 399.5 + 141.2 + 294.8 = $277 Mil.
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Total Receivables was $2,818 Mil.
Revenue was 918 + 1146.1 + 981.9 + 1014.5 = $4,061 Mil.
Gross Profit was 339.7 + 435.7 + 381.2 + 432.8 = $1,589 Mil.
Total Current Assets was $5,198 Mil.
Total Assets was $11,978 Mil.
Property, Plant and Equipment(Net PPE) was $876 Mil.
Depreciation, Depletion and Amortization(DDA) was $185 Mil.
Selling, General, & Admin. Expense(SGA) was $712 Mil.
Total Current Liabilities was $3,553 Mil.
Long-Term Debt & Capital Lease Obligation was $3,025 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) |
| = | (2900.1 / 4119.5) | / | (2817.9 / 4060.5) |
| = | 0.703993 | / | 0.693979 |
| | = | 1.0144 |
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) |
| = | (1589.4 / 4060.5) | / | (1625.9 / 4119.5) |
| = | 0.39143 | / | 0.394684 |
| | = | 0.9918 |
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 - (5077.6 + 858.7) / 11800.9) | / | (1 - (5198 + 875.6) / 11978.4) |
| = | 0.496962 | / | 0.492954 |
| | = | 1.0081 |
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 |
| = | 4119.5 | / | 4060.5 |
| | = | 1.0145 |
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)) |
| = | (185.3 / (185.3 + 875.6)) | / | (174.3 / (174.3 + 858.7)) |
| = | 0.174663 | / | 0.168732 |
| | = | 1.0352 |
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) |
| = | (652.7 / 4119.5) | / | (712.3 / 4060.5) |
| = | 0.158442 | / | 0.175422 |
| | = | 0.9032 |
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) |
| = | ((3027.7 + 3305.3) / 11800.9) | / | ((3024.6 + 3552.9) / 11978.4) |
| = | 0.536654 | / | 0.549113 |
| | = | 0.9773 |
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 |
| = | (328.3 - -133.4 | - | 277.2) | / | 11800.9 |
| | = | 0.015634 |
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.
FMC has a M-score of -2.35 suggests that the company is unlikely to be a manipulator.
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