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 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.41 |
-2.41 |
-2.39 |
-2.26 |
-1.67 |
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FMC 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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-2.26 |
-2.15 |
-2.38 |
-2.28 |
-1.67 |
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 * 1.2513 | + | 0.528 * 0.9827 | + | 0.404 * 1.1381 | + | 0.892 * 0.7733 | + | 0.115 * 0.964 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2416 | + | 4.679 * 0.161007 | - | 0.327 * 0.9184 |
| = | -1.67 |
* 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 $2,945 Mil.
Revenue was 1146.1 + 981.9 + 1014.5 + 1344.3 = $4,487 Mil.
Gross Profit was 435.7 + 381.2 + 432.8 + 581.3 = $1,831 Mil.
Total Current Assets was $5,129 Mil.
Total Assets was $11,926 Mil.
Property, Plant and Equipment(Net PPE) was $1,014 Mil.
Depreciation, Depletion and Amortization(DDA) was $184 Mil.
Selling, General, & Admin. Expense(SGA) was $753 Mil.
Total Current Liabilities was $3,385 Mil.
Long-Term Debt & Capital Lease Obligation was $3,147 Mil.
Net Income was 1098.5 + -3.5 + 30.5 + 196 = $1,322 Mil.
Non Operating Income was -150.9 + -32.4 + -11.9 + -17.1 = $-212 Mil.
Cash Flow from Operations was 292.8 + 67.5 + 117.2 + -863.9 = $-386 Mil.
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Total Receivables was $3,044 Mil.
Revenue was 1622 + 1377.2 + 1452.3 + 1350.8 = $5,802 Mil.
Gross Profit was 685.6 + 477.5 + 591 + 572.7 = $2,327 Mil.
Total Current Assets was $5,439 Mil.
Total Assets was $11,171 Mil.
Property, Plant and Equipment(Net PPE) was $973 Mil.
Depreciation, Depletion and Amortization(DDA) was $169 Mil.
Selling, General, & Admin. Expense(SGA) was $784 Mil.
Total Current Liabilities was $3,800 Mil.
Long-Term Debt & Capital Lease Obligation was $2,862 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) |
| = | (2945.1 / 4486.8) | / | (3043.8 / 5802.3) |
| = | 0.656392 | / | 0.524585 |
| | = | 1.2513 |
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) |
| = | (2326.8 / 5802.3) | / | (1831 / 4486.8) |
| = | 0.401013 | / | 0.408086 |
| | = | 0.9827 |
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 - (5129.1 + 1014.3) / 11926.2) | / | (1 - (5438.6 + 973.4) / 11171.3) |
| = | 0.484882 | / | 0.426029 |
| | = | 1.1381 |
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 |
| = | 4486.8 | / | 5802.3 |
| | = | 0.7733 |
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)) |
| = | (169.4 / (169.4 + 973.4)) | / | (184.3 / (184.3 + 1014.3)) |
| = | 0.148232 | / | 0.153763 |
| | = | 0.964 |
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) |
| = | (752.5 / 4486.8) | / | (783.8 / 5802.3) |
| = | 0.167714 | / | 0.135084 |
| | = | 1.2416 |
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) |
| = | ((3146.8 + 3384.6) / 11926.2) | / | ((2861.8 + 3799.6) / 11171.3) |
| = | 0.547651 | / | 0.596296 |
| | = | 0.9184 |
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 |
| = | (1321.5 - -212.3 | - | -386.4) | / | 11926.2 |
| | = | 0.161007 |
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 -1.67 signals that the company is likely to be a manipulator.
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