Schneider National Beneish M-Score Historical Data
The historical data trend for Schneider National'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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Schneider National Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.02 |
-2.86 |
-2.42 |
-2.97 |
-2.69 |
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Schneider National 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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-2.97 |
-2.98 |
-2.86 |
-2.77 |
-2.69 |
Competitive Comparison
For the Trucking subindustry, Schneider National'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.
Schneider National Beneish M-Score Distribution
For the Transportation industry and Industrials sector, Schneider National's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Schneider National's Beneish M-Score falls into.
Schneider National 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 Schneider National 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 * 1.1309 | + | 0.528 * 1.3701 | + | 0.404 * 1.191 | + | 0.892 * 0.8326 | + | 0.115 * 1.0313 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9868 | + | 4.679 * -0.100588 | - | 0.327 * 0.9781 |
| = | -2.69 |
* 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 $731 Mil.
Revenue was 1371.7 + 1352 + 1346.5 + 1428.7 = $5,499 Mil.
Gross Profit was 105.1 + 120.6 + 158.6 + 175.1 = $559 Mil.
Total Current Assets was $1,111 Mil.
Total Assets was $4,557 Mil.
Property, Plant and Equipment(Net PPE) was $2,582 Mil.
Depreciation, Depletion and Amortization(DDA) was $383 Mil.
Selling, General, & Admin. Expense(SGA) was $263 Mil.
Total Current Liabilities was $606 Mil.
Long-Term Debt & Capital Lease Obligation was $198 Mil.
Net Income was 27.4 + 35.6 + 77.5 + 98 = $239 Mil.
Non Operating Income was -0.4 + 1.1 + -0.8 + 17 = $17 Mil.
Cash Flow from Operations was 193.9 + 182.9 + 120.1 + 183.1 = $680 Mil.
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Total Receivables was $776 Mil.
Revenue was 1561.7 + 1675.3 + 1746.9 + 1620.5 = $6,604 Mil.
Gross Profit was 207.4 + 213 + 240.7 + 259.4 = $921 Mil.
Total Current Assets was $1,350 Mil.
Total Assets was $4,318 Mil.
Property, Plant and Equipment(Net PPE) was $2,280 Mil.
Depreciation, Depletion and Amortization(DDA) was $350 Mil.
Selling, General, & Admin. Expense(SGA) was $320 Mil.
Total Current Liabilities was $637 Mil.
Long-Term Debt & Capital Lease Obligation was $142 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) |
| = | (730.9 / 5498.9) | / | (776.2 / 6604.4) |
| = | 0.132917 | / | 0.117528 |
| | = | 1.1309 |
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) |
| = | (920.5 / 6604.4) | / | (559.4 / 5498.9) |
| = | 0.139377 | / | 0.101729 |
| | = | 1.3701 |
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 - (1110.9 + 2581.7) / 4557.2) | / | (1 - (1350.3 + 2280) / 4318.2) |
| = | 0.189722 | / | 0.159302 |
| | = | 1.191 |
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 |
| = | 5498.9 | / | 6604.4 |
| | = | 0.8326 |
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)) |
| = | (350 / (350 + 2280)) | / | (382.5 / (382.5 + 2581.7)) |
| = | 0.13308 | / | 0.12904 |
| | = | 1.0313 |
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) |
| = | (263 / 5498.9) | / | (320.1 / 6604.4) |
| = | 0.047828 | / | 0.048468 |
| | = | 0.9868 |
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) |
| = | ((197.6 + 606.2) / 4557.2) | / | ((141.8 + 636.9) / 4318.2) |
| = | 0.17638 | / | 0.18033 |
| | = | 0.9781 |
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 |
| = | (238.5 - 16.9 | - | 680) | / | 4557.2 |
| | = | -0.100588 |
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.
Schneider National has a M-score of -2.69 suggests that the company is unlikely to be a manipulator.
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