Trimble Beneish M-Score Historical Data
The historical data trend for Trimble'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.
Trimble Beneish M-Score Chart
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Trimble Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.64 |
-2.65 |
-2.53 |
-2.67 |
-2.76 |
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Trimble 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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-2.67 |
-2.64 |
-2.96 |
-2.97 |
-2.76 |
Competitive Comparison of Trimble's Beneish M-Score
For the Scientific & Technical Instruments subindustry, Trimble'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.
Trimble's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Trimble's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Trimble's Beneish M-Score falls into.
Trimble 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 Trimble 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 * 1.1041 | + | 0.528 * 0.9434 | + | 0.404 * 0.9406 | + | 0.892 * 0.9688 | + | 0.115 * 1.0428 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1099 | + | 4.679 * -0.065972 | - | 0.327 * 0.7398 |
| = | -2.70 |
* 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 €693 Mil.
Revenue was 939.147 + 789.096 + 808.973 + 877.036 = €3,414 Mil.
Gross Profit was 650.546 + 518.616 + 507.141 + 546.112 = €2,222 Mil.
Total Current Assets was €2,168 Mil.
Total Assets was €9,061 Mil.
Property, Plant and Equipment(Net PPE) was €298 Mil.
Depreciation, Depletion and Amortization(DDA) was €215 Mil.
Selling, General, & Admin. Expense(SGA) was €1,068 Mil.
Total Current Liabilities was €1,708 Mil.
Long-Term Debt & Capital Lease Obligation was €1,446 Mil.
Net Income was 86.141 + 36.581 + 1222.936 + 52.624 = €1,398 Mil.
Non Operating Income was -61.311 + -28.472 + 1591.749 + 2.208 = €1,504 Mil.
Cash Flow from Operations was 109.921 + 85.505 + 81.38 + 215.096 = €492 Mil.
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Total Receivables was €648 Mil.
Revenue was 855.011 + 896.99 + 917.093 + 854.984 = €3,524 Mil.
Gross Profit was 529.384 + 553.017 + 557.954 + 523.787 = €2,164 Mil.
Total Current Assets was €1,679 Mil.
Total Assets was €8,748 Mil.
Property, Plant and Equipment(Net PPE) was €299 Mil.
Depreciation, Depletion and Amortization(DDA) was €232 Mil.
Selling, General, & Admin. Expense(SGA) was €993 Mil.
Total Current Liabilities was €1,677 Mil.
Long-Term Debt & Capital Lease Obligation was €2,437 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) |
| = | (693.139 / 3414.252) | / | (647.952 / 3524.078) |
| = | 0.203013 | / | 0.183864 |
| | = | 1.1041 |
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) |
| = | (2164.142 / 3524.078) | / | (2222.415 / 3414.252) |
| = | 0.614102 | / | 0.650923 |
| | = | 0.9434 |
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 - (2168.232 + 297.865) / 9061.327) | / | (1 - (1678.935 + 299.4) / 8747.538) |
| = | 0.727844 | / | 0.773841 |
| | = | 0.9406 |
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 |
| = | 3414.252 | / | 3524.078 |
| | = | 0.9688 |
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)) |
| = | (232.361 / (232.361 + 299.4)) | / | (214.839 / (214.839 + 297.865)) |
| = | 0.436965 | / | 0.419031 |
| | = | 1.0428 |
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) |
| = | (1067.638 / 3414.252) | / | (992.88 / 3524.078) |
| = | 0.3127 | / | 0.281742 |
| | = | 1.1099 |
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) |
| = | ((1445.87 + 1707.54) / 9061.327) | / | ((2437.478 + 1677.468) / 8747.538) |
| = | 0.348008 | / | 0.470412 |
| | = | 0.7398 |
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 |
| = | (1398.282 - 1504.174 | - | 491.902) | / | 9061.327 |
| | = | -0.065972 |
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.
Trimble has a M-score of -2.70 suggests that the company is unlikely to be a manipulator.
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