Corteva Beneish M-Score Historical Data
The historical data trend for Corteva'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.
Corteva Beneish M-Score Chart
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Corteva Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.77 |
-2.77 |
-2.26 |
-2.54 |
-2.53 |
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Corteva 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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-2.54 |
-2.67 |
-2.47 |
-2.44 |
-2.53 |
Competitive Comparison of Corteva's Beneish M-Score
For the Agricultural Inputs subindustry, Corteva'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.
Corteva's Beneish M-Score Distribution in the Agriculture Industry
For the Agriculture industry and Basic Materials sector, Corteva's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Corteva's Beneish M-Score falls into.
Corteva 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 Corteva 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 * 1.208 | + | 0.528 * 0.9789 | + | 0.404 * 1.0147 | + | 0.892 * 1.052 | + | 0.115 * 1.0533 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0294 | + | 4.679 * -0.033054 | - | 0.327 * 1.0232 |
| = | -2.41 |
* 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 MXN118,377 Mil.
Revenue was 82963.975 + 45799.638 + 111972.47 + 74550.377 = MXN315,286 Mil.
Gross Profit was 30908.147 + 14984.318 + 58514.409 + 32229.927 = MXN136,637 Mil.
Total Current Assets was MXN314,859 Mil.
Total Assets was MXN851,434 Mil.
Property, Plant and Equipment(Net PPE) was MXN85,488 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN23,135 Mil.
Selling, General, & Admin. Expense(SGA) was MXN59,778 Mil.
Total Current Liabilities was MXN216,607 Mil.
Long-Term Debt & Capital Lease Obligation was MXN40,731 Mil.
Net Income was -855.084 + -10317.717 + 19291.068 + 6953.831 = MXN15,072 Mil.
Non Operating Income was -4546.543 + -2658.191 + -3554.1 + -2871.152 = MXN-13,630 Mil.
Cash Flow from Operations was 110097.24 + -4804.433 + -5147.949 + -43299.629 = MXN56,845 Mil.
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Total Receivables was MXN93,155 Mil.
Revenue was 62923.537 + 45114.943 + 103634.876 + 88034.1 = MXN299,707 Mil.
Gross Profit was 22762.467 + 16443.439 + 49854.461 + 38086.825 = MXN127,147 Mil.
Total Current Assets was MXN276,001 Mil.
Total Assets was MXN729,825 Mil.
Property, Plant and Equipment(Net PPE) was MXN72,769 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN21,045 Mil.
Selling, General, & Admin. Expense(SGA) was MXN55,199 Mil.
Total Current Liabilities was MXN176,685 Mil.
Long-Term Debt & Capital Lease Obligation was MXN38,888 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) |
| = | (118376.953 / 315286.46) | / | (93154.673 / 299707.456) |
| = | 0.375458 | / | 0.310819 |
| | = | 1.208 |
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) |
| = | (127147.192 / 299707.456) | / | (136636.801 / 315286.46) |
| = | 0.424238 | / | 0.433374 |
| | = | 0.9789 |
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 - (314858.503 + 85487.514) / 851433.952) | / | (1 - (276001.272 + 72768.601) / 729824.767) |
| = | 0.529798 | / | 0.522118 |
| | = | 1.0147 |
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 |
| = | 315286.46 | / | 299707.456 |
| | = | 1.052 |
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)) |
| = | (21045.355 / (21045.355 + 72768.601)) | / | (23134.575 / (23134.575 + 85487.514)) |
| = | 0.224331 | / | 0.212982 |
| | = | 1.0533 |
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) |
| = | (59777.621 / 315286.46) | / | (55199.262 / 299707.456) |
| = | 0.189598 | / | 0.184177 |
| | = | 1.0294 |
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) |
| = | ((40731.182 + 216607.3) / 851433.952) | / | ((38888.002 + 176684.947) / 729824.767) |
| = | 0.302241 | / | 0.295376 |
| | = | 1.0232 |
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 |
| = | (15072.098 - -13629.986 | - | 56845.229) | / | 851433.952 |
| | = | -0.033054 |
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.
Corteva has a M-score of -2.41 suggests that the company is unlikely to be a manipulator.
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