Terex Beneish M-Score Historical Data
The historical data trend for Terex'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.
Terex Beneish M-Score Chart
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Terex Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.74 |
-2.27 |
-2.34 |
-2.41 |
-1.89 |
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Terex 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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-2.41 |
-2.30 |
-2.24 |
-2.20 |
-1.89 |
Competitive Comparison of Terex's Beneish M-Score
For the Farm & Heavy Construction Machinery subindustry, Terex'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.
Terex's Beneish M-Score Distribution in the Farm & Heavy Construction Machinery Industry
For the Farm & Heavy Construction Machinery industry and Industrials sector, Terex's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Terex's Beneish M-Score falls into.
Terex 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 Terex 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 * 1.179 | + | 0.528 * 1.0967 | + | 0.404 * 2.1261 | + | 0.892 * 0.9952 | + | 0.115 * 0.8684 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0072 | + | 4.679 * 0.009075 | - | 0.327 * 1.3253 |
| = | -1.89 |
* 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 $643 Mil.
Revenue was 1241 + 1212 + 1381.7 + 1292.5 = $5,127 Mil.
Gross Profit was 197 + 245 + 328.4 + 297.3 = $1,068 Mil.
Total Current Assets was $2,320 Mil.
Total Assets was $5,730 Mil.
Property, Plant and Equipment(Net PPE) was $714 Mil.
Depreciation, Depletion and Amortization(DDA) was $82 Mil.
Selling, General, & Admin. Expense(SGA) was $541 Mil.
Total Current Liabilities was $1,073 Mil.
Long-Term Debt & Capital Lease Obligation was $2,580 Mil.
Net Income was -2 + 88 + 140.7 + 108.5 = $335 Mil.
Non Operating Income was -14 + -13 + -5.4 + -10.4 = $-43 Mil.
Cash Flow from Operations was 177 + 116.4 + 66.5 + -33.9 = $326 Mil.
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Total Receivables was $548 Mil.
Revenue was 1223 + 1290 + 1403.1 + 1235.7 = $5,152 Mil.
Gross Profit was 263 + 292 + 342.9 + 278.7 = $1,177 Mil.
Total Current Assets was $2,245 Mil.
Total Assets was $3,615 Mil.
Property, Plant and Equipment(Net PPE) was $570 Mil.
Depreciation, Depletion and Amortization(DDA) was $56 Mil.
Selling, General, & Admin. Expense(SGA) was $540 Mil.
Total Current Liabilities was $1,119 Mil.
Long-Term Debt & Capital Lease Obligation was $620 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) |
| = | (643 / 5127.2) | / | (548 / 5151.8) |
| = | 0.12541 | / | 0.106371 |
| | = | 1.179 |
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) |
| = | (1176.6 / 5151.8) | / | (1067.7 / 5127.2) |
| = | 0.228386 | / | 0.208242 |
| | = | 1.0967 |
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 - (2320 + 714) / 5730) | / | (1 - (2245 + 570) / 3615) |
| = | 0.470506 | / | 0.2213 |
| | = | 2.1261 |
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 |
| = | 5127.2 | / | 5151.8 |
| | = | 0.9952 |
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)) |
| = | (56 / (56 + 570)) | / | (82 / (82 + 714)) |
| = | 0.089457 | / | 0.103015 |
| | = | 0.8684 |
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) |
| = | (541.3 / 5127.2) | / | (540 / 5151.8) |
| = | 0.105574 | / | 0.104818 |
| | = | 1.0072 |
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) |
| = | ((2580 + 1073) / 5730) | / | ((620 + 1119) / 3615) |
| = | 0.637522 | / | 0.481051 |
| | = | 1.3253 |
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 |
| = | (335.2 - -42.8 | - | 326) | / | 5730 |
| | = | 0.009075 |
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.
Terex has a M-score of -1.89 suggests that the company is unlikely to be a manipulator.
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