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.
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Corteva Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
Array
(
[0] => -
[1] => -
[2] => -
[3] => -2.72
[4] => -2.77
[5] => -2.77
[6] => -2.26
[7] => -2.53
)
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|
|
|
-2.72 |
-2.77 |
-2.77 |
-2.26 |
-2.53 |
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Corteva 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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|
|
|
|
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|
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|
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-2.26 |
-2.23 |
-2.26 |
-2.36 |
-2.53 |
Competitive Comparison
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 Beneish M-Score Distribution
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 * 0.9754 | + | 0.528 * 0.9481 | + | 0.404 * 1.0316 | + | 0.892 * 0.9869 | + | 0.115 * 1.0138 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9948 | + | 4.679 * 0.002186 | - | 0.327 * 1.0467 |
| = | -2.53 |
* 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 $5,488 Mil.
Revenue was 3707 + 2590 + 6045 + 4884 = $17,226 Mil.
Gross Profit was 1341 + 944 + 2908 + 2113 = $7,306 Mil.
Total Current Assets was $16,260 Mil.
Total Assets was $42,996 Mil.
Property, Plant and Equipment(Net PPE) was $4,287 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,211 Mil.
Selling, General, & Admin. Expense(SGA) was $3,115 Mil.
Total Current Liabilities was $10,409 Mil.
Long-Term Debt & Capital Lease Obligation was $2,291 Mil.
Net Income was -253 + -321 + 714 + 595 = $735 Mil.
Non Operating Income was -556 + -180 + -248 + -144 = $-1,128 Mil.
Cash Flow from Operations was 4384 + -116 + 807 + -3306 = $1,769 Mil.
|
Total Receivables was $5,701 Mil.
Revenue was 3825 + 2777 + 6252 + 4601 = $17,455 Mil.
Gross Profit was 1315 + 898 + 2929 + 1877 = $7,019 Mil.
Total Current Assets was $16,795 Mil.
Total Assets was $42,618 Mil.
Property, Plant and Equipment(Net PPE) was $4,254 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,223 Mil.
Selling, General, & Admin. Expense(SGA) was $3,173 Mil.
Total Current Liabilities was $10,744 Mil.
Long-Term Debt & Capital Lease Obligation was $1,283 Mil.
|
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) |
| = | (5488 / 17226) | / | (5701 / 17455) |
| = | 0.318588 | / | 0.326611 |
| | = | 0.9754 |
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) |
| = | (7019 / 17455) | / | (7306 / 17226) |
| = | 0.40212 | / | 0.424126 |
| | = | 0.9481 |
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 - (16260 + 4287) / 42996) | / | (1 - (16795 + 4254) / 42618) |
| = | 0.522118 | / | 0.506101 |
| | = | 1.0316 |
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 |
| = | 17226 | / | 17455 |
| | = | 0.9869 |
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)) |
| = | (1223 / (1223 + 4254)) | / | (1211 / (1211 + 4287)) |
| = | 0.223297 | / | 0.220262 |
| | = | 1.0138 |
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) |
| = | (3115 / 17226) | / | (3173 / 17455) |
| = | 0.180831 | / | 0.181782 |
| | = | 0.9948 |
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) |
| = | ((2291 + 10409) / 42996) | / | ((1283 + 10744) / 42618) |
| = | 0.295376 | / | 0.282205 |
| | = | 1.0467 |
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 |
| = | (735 - -1128 | - | 1769) | / | 42996 |
| | = | 0.002186 |
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 -2.53 suggests that the company is unlikely to be a manipulator.
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