AGCO Beneish M-Score Historical Data
The historical data trend for AGCO'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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AGCO Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.80 |
-2.67 |
-2.19 |
-2.19 |
-2.06 |
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AGCO 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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-2.19 |
-2.07 |
-1.99 |
-2.14 |
-2.06 |
Competitive Comparison
For the Farm & Heavy Construction Machinery subindustry, AGCO'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.
AGCO Beneish M-Score Distribution
For the Farm & Heavy Construction Machinery industry and Industrials sector, AGCO's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AGCO's Beneish M-Score falls into.
AGCO 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 AGCO 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 * 1.1538 | + | 0.528 * 0.9051 | + | 0.404 * 1.0114 | + | 0.892 * 1.1392 | + | 0.115 * 1.1024 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0734 | + | 4.679 * 0.039103 | - | 0.327 * 0.9455 |
| = | -2.06 |
* 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 $1,605 Mil.
Revenue was 3800.7 + 3455.5 + 3822.7 + 3333.5 = $14,412 Mil.
Gross Profit was 982.8 + 934 + 1005.7 + 854.9 = $3,777 Mil.
Total Current Assets was $6,341 Mil.
Total Assets was $11,421 Mil.
Property, Plant and Equipment(Net PPE) was $2,097 Mil.
Depreciation, Depletion and Amortization(DDA) was $288 Mil.
Selling, General, & Admin. Expense(SGA) was $1,455 Mil.
Total Current Liabilities was $4,344 Mil.
Long-Term Debt & Capital Lease Obligation was $1,512 Mil.
Net Income was 339 + 280.6 + 319.2 + 232.6 = $1,171 Mil.
Non Operating Income was -152.9 + -87 + -85.1 + -53.3 = $-378 Mil.
Cash Flow from Operations was 900.4 + 567.7 + 192.1 + -557.1 = $1,103 Mil.
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Total Receivables was $1,221 Mil.
Revenue was 3898.9 + 3121.6 + 2945.2 + 2685.7 = $12,651 Mil.
Gross Profit was 940.6 + 738.9 + 690.5 + 631.3 = $3,001 Mil.
Total Current Assets was $5,739 Mil.
Total Assets was $10,104 Mil.
Property, Plant and Equipment(Net PPE) was $1,755 Mil.
Depreciation, Depletion and Amortization(DDA) was $270 Mil.
Selling, General, & Admin. Expense(SGA) was $1,190 Mil.
Total Current Liabilities was $4,088 Mil.
Long-Term Debt & Capital Lease Obligation was $1,390 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) |
| = | (1605.3 / 14412.4) | / | (1221.3 / 12651.4) |
| = | 0.111383 | / | 0.096535 |
| | = | 1.1538 |
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) |
| = | (3001.3 / 12651.4) | / | (3777.4 / 14412.4) |
| = | 0.237231 | / | 0.262094 |
| | = | 0.9051 |
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 - (6340.8 + 2097.1) / 11421.2) | / | (1 - (5739.3 + 1755.1) / 10103.7) |
| = | 0.261207 | / | 0.258252 |
| | = | 1.0114 |
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 |
| = | 14412.4 | / | 12651.4 |
| | = | 1.1392 |
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)) |
| = | (269.6 / (269.6 + 1755.1)) | / | (288.1 / (288.1 + 2097.1)) |
| = | 0.133156 | / | 0.120787 |
| | = | 1.1024 |
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) |
| = | (1454.5 / 14412.4) | / | (1189.5 / 12651.4) |
| = | 0.10092 | / | 0.094021 |
| | = | 1.0734 |
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) |
| = | ((1511.6 + 4343.6) / 11421.2) | / | ((1390.2 + 4088) / 10103.7) |
| = | 0.512661 | / | 0.542197 |
| | = | 0.9455 |
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 |
| = | (1171.4 - -378.3 | - | 1103.1) | / | 11421.2 |
| | = | 0.039103 |
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.
AGCO has a M-score of -2.06 suggests that the company is unlikely to be a manipulator.
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