Werner Enterprises Beneish M-Score Historical Data
The historical data trend for Werner Enterprises'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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Werner Enterprises Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.14 |
-3.14 |
-2.03 |
-2.65 |
-2.98 |
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Werner Enterprises 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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-2.65 |
-2.72 |
-2.95 |
-2.86 |
-2.98 |
Competitive Comparison
For the Trucking subindustry, Werner Enterprises'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.
Werner Enterprises Beneish M-Score Distribution
For the Transportation industry and Industrials sector, Werner Enterprises's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Werner Enterprises's Beneish M-Score falls into.
Werner Enterprises 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 Werner Enterprises 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 * 0.8591 | + | 0.528 * 1.2287 | + | 0.404 * 1.0597 | + | 0.892 * 0.998 | + | 0.115 * 1.0089 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9638 | + | 4.679 * -0.114056 | - | 0.327 * 0.9609 |
| = | -2.98 |
* 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 $470 Mil.
Revenue was 821.945 + 817.744 + 811.096 + 832.714 = $3,283 Mil.
Gross Profit was 103.397 + 99.998 + 110.035 + 110.223 = $424 Mil.
Total Current Assets was $635 Mil.
Total Assets was $3,158 Mil.
Property, Plant and Equipment(Net PPE) was $1,973 Mil.
Depreciation, Depletion and Amortization(DDA) was $300 Mil.
Selling, General, & Admin. Expense(SGA) was $157 Mil.
Total Current Liabilities was $331 Mil.
Long-Term Debt & Capital Lease Obligation was $646 Mil.
Net Income was 23.573 + 23.704 + 29.881 + 35.224 = $112 Mil.
Non Operating Income was -0.434 + -0.428 + -0.851 + -0.088 = $-2 Mil.
Cash Flow from Operations was 118.347 + 74.229 + 114.943 + 166.847 = $474 Mil.
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Total Receivables was $549 Mil.
Revenue was 861.491 + 827.606 + 836.276 + 764.605 = $3,290 Mil.
Gross Profit was 142.619 + 125.323 + 128.948 + 124.697 = $522 Mil.
Total Current Assets was $763 Mil.
Total Assets was $3,097 Mil.
Property, Plant and Equipment(Net PPE) was $1,825 Mil.
Depreciation, Depletion and Amortization(DDA) was $280 Mil.
Selling, General, & Admin. Expense(SGA) was $163 Mil.
Total Current Liabilities was $310 Mil.
Long-Term Debt & Capital Lease Obligation was $688 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) |
| = | (470.423 / 3283.499) | / | (548.69 / 3289.978) |
| = | 0.143269 | / | 0.166776 |
| | = | 0.8591 |
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) |
| = | (521.587 / 3289.978) | / | (423.653 / 3283.499) |
| = | 0.158538 | / | 0.129025 |
| | = | 1.2287 |
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 - (634.628 + 1972.956) / 3157.936) | / | (1 - (762.615 + 1825.276) / 3097.255) |
| = | 0.174276 | / | 0.164457 |
| | = | 1.0597 |
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 |
| = | 3283.499 | / | 3289.978 |
| | = | 0.998 |
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)) |
| = | (279.923 / (279.923 + 1825.276)) | / | (299.509 / (299.509 + 1972.956)) |
| = | 0.132967 | / | 0.131799 |
| | = | 1.0089 |
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) |
| = | (156.996 / 3283.499) | / | (163.221 / 3289.978) |
| = | 0.047814 | / | 0.049612 |
| | = | 0.9638 |
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) |
| = | ((646.25 + 330.585) / 3157.936) | / | ((687.5 + 309.52) / 3097.255) |
| = | 0.309327 | / | 0.321904 |
| | = | 0.9609 |
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 |
| = | (112.382 - -1.801 | - | 474.366) | / | 3157.936 |
| | = | -0.114056 |
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.
Werner Enterprises has a M-score of -2.98 suggests that the company is unlikely to be a manipulator.
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