Caterpillar Beneish M-Score Historical Data
The historical data trend for Caterpillar'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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Caterpillar Annual Data
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Trend |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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|
|
|
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-2.78 |
-2.44 |
-2.48 |
-2.67 |
-2.58 |
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Caterpillar Quarterly Data
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Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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|
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|
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-2.63 |
-2.65 |
-2.58 |
-2.42 |
-2.47 |
Competitive Comparison
For the Farm & Heavy Construction Machinery subindustry, Caterpillar'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.
Caterpillar Beneish M-Score Distribution
For the Farm & Heavy Construction Machinery industry and Industrials sector, Caterpillar's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Caterpillar's Beneish M-Score falls into.
Caterpillar 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 Caterpillar 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 * 0.847 | + | 0.528 * 1.0517 | + | 0.404 * 1.0315 | + | 0.892 * 1.1774 | + | 0.115 * 1.0147 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9504 | + | 4.679 * -0.0092 | - | 0.327 * 1.0348 |
| = | -2.47 |
* 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 (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $17,315 Mil.
Revenue was 14247 + 13589 + 13798 + 12397 = $54,031 Mil.
Gross Profit was 4152 + 3924 + 3692 + 3669 = $15,437 Mil.
Total Current Assets was $41,982 Mil.
Total Assets was $81,107 Mil.
Property, Plant and Equipment(Net PPE) was $11,744 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,289 Mil.
Selling, General, & Admin. Expense(SGA) was $5,533 Mil.
Total Current Liabilities was $28,963 Mil.
Long-Term Debt & Capital Lease Obligation was $26,219 Mil.
Net Income was 1673 + 1537 + 2120 + 1426 = $6,756 Mil.
Non Operating Income was 260 + 253 + 1063 + 225 = $1,801 Mil.
Cash Flow from Operations was 2233 + 313 + 1412 + 1740 = $5,698 Mil.
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Total Receivables was $17,363 Mil.
Revenue was 12889 + 11887 + 11235 + 9881 = $45,892 Mil.
Gross Profit was 3892 + 3750 + 3323 + 2825 = $13,790 Mil.
Total Current Assets was $42,946 Mil.
Total Assets was $81,697 Mil.
Property, Plant and Equipment(Net PPE) was $12,014 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,383 Mil.
Selling, General, & Admin. Expense(SGA) was $4,945 Mil.
Total Current Liabilities was $27,508 Mil.
Long-Term Debt & Capital Lease Obligation was $26,204 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) |
| = | (17315 / 54031) | / | (17363 / 45892) |
| = | 0.32046418 | / | 0.37834481 |
| | = | 0.847 |
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) |
| = | (13790 / 45892) | / | (15437 / 54031) |
| = | 0.3004881 | / | 0.28570635 |
| | = | 1.0517 |
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 - (41982 + 11744) / 81107) | / | (1 - (42946 + 12014) / 81697) |
| = | 0.33759108 | / | 0.32727028 |
| | = | 1.0315 |
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 |
| = | 54031 | / | 45892 |
| | = | 1.1774 |
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)) |
| = | (2383 / (2383 + 12014)) | / | (2289 / (2289 + 11744)) |
| = | 0.16552059 | / | 0.16311551 |
| | = | 1.0147 |
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) |
| = | (5533 / 54031) | / | (4945 / 45892) |
| = | 0.10240418 | / | 0.10775299 |
| | = | 0.9504 |
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) |
| = | ((26219 + 28963) / 81107) | / | ((26204 + 27508) / 81697) |
| = | 0.68036051 | / | 0.65745376 |
| | = | 1.0348 |
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 |
| = | (6756 - 1801 | - | 5698) | / | 81107 |
| | = | -0.0092 |
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.
Caterpillar has a M-score of -2.47 suggests that the company is unlikely to be a manipulator.
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