Deere Beneish M-Score Historical Data
The historical data trend for Deere'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.
Deere Beneish M-Score Chart
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Deere Annual Data
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Trend |
Oct14 |
Oct15 |
Oct16 |
Oct17 |
Oct18 |
Oct19 |
Oct20 |
Oct21 |
Oct22 |
Oct23 |
| Beneish M-Score |
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-2.50 |
-2.86 |
-2.45 |
-2.26 |
-2.41 |
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Deere Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-2.26 |
-2.27 |
-2.28 |
-2.41 |
-2.46 |
Competitive Comparison of Deere's Beneish M-Score
For the Farm & Heavy Construction Machinery subindustry, Deere'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.
Deere's Beneish M-Score Distribution in the Farm & Heavy Construction Machinery Industry
For the Farm & Heavy Construction Machinery industry and Industrials sector, Deere's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Deere's Beneish M-Score falls into.
Deere 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 Deere 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 * 1.0577 | + | 0.528 * 0.8575 | + | 0.404 * 0.913 | + | 0.892 * 1.0984 | + | 0.115 * 1.0066 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0551 | + | 4.679 * 0.000651 | - | 0.327 * 1.0297 |
| = | -2.46 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was $59,920 Mil.
Revenue was 11846 + 15157 + 15537 + 17158 = $59,698 Mil.
Gross Profit was 4646 + 5503 + 5913 + 6428 = $22,490 Mil.
Total Current Assets was $75,130 Mil.
Total Assets was $101,371 Mil.
Property, Plant and Equipment(Net PPE) was $13,665 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,030 Mil.
Selling, General, & Admin. Expense(SGA) was $4,732 Mil.
Total Current Liabilities was $36,594 Mil.
Long-Term Debt & Capital Lease Obligation was $39,933 Mil.
Net Income was 1751 + 2369 + 2978 + 2860 = $9,958 Mil.
Non Operating Income was 339 + 133 + 264 + 229 = $965 Mil.
Cash Flow from Operations was -908 + 5693 + 3043 + 1099 = $8,927 Mil.
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Total Receivables was $51,572 Mil.
Revenue was 12396 + 15276 + 13846 + 12830 = $54,348 Mil.
Gross Profit was 4462 + 4848 + 4335 + 3912 = $17,557 Mil.
Total Current Assets was $66,456 Mil.
Total Assets was $91,620 Mil.
Property, Plant and Equipment(Net PPE) was $12,714 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,903 Mil.
Selling, General, & Admin. Expense(SGA) was $4,083 Mil.
Total Current Liabilities was $32,101 Mil.
Long-Term Debt & Capital Lease Obligation was $35,071 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) |
| = | (59920 / 59698) | / | (51572 / 54348) |
| = | 1.003719 | / | 0.948922 |
| | = | 1.0577 |
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) |
| = | (17557 / 54348) | / | (22490 / 59698) |
| = | 0.323048 | / | 0.37673 |
| | = | 0.8575 |
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 - (75130 + 13665) / 101371) | / | (1 - (66456 + 12714) / 91620) |
| = | 0.124059 | / | 0.135887 |
| | = | 0.913 |
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 |
| = | 59698 | / | 54348 |
| | = | 1.0984 |
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)) |
| = | (1903 / (1903 + 12714)) | / | (2030 / (2030 + 13665)) |
| = | 0.130191 | / | 0.129341 |
| | = | 1.0066 |
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) |
| = | (4732 / 59698) | / | (4083 / 54348) |
| = | 0.079266 | / | 0.075127 |
| | = | 1.0551 |
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) |
| = | ((39933 + 36594) / 101371) | / | ((35071 + 32101) / 91620) |
| = | 0.75492 | / | 0.733159 |
| | = | 1.0297 |
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 |
| = | (9958 - 965 | - | 8927) | / | 101371 |
| | = | 0.000651 |
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.
Deere has a M-score of -2.46 suggests that the company is unlikely to be a manipulator.
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