Saia Beneish M-Score Historical Data
The historical data trend for Saia'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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Saia Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.04 |
-3.01 |
-2.53 |
-2.57 |
-2.84 |
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Saia 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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-2.57 |
-2.77 |
-3.11 |
-2.84 |
-2.84 |
Competitive Comparison
For the Trucking subindustry, Saia'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.
Saia Beneish M-Score Distribution
For the Transportation industry and Industrials sector, Saia's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Saia's Beneish M-Score falls into.
Saia 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 Saia 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 * 0.9659 | + | 0.528 * 1.0183 | + | 0.404 * 1.0913 | + | 0.892 * 1.032 | + | 0.115 * 1.0291 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1639 | + | 4.679 * -0.0872 | - | 0.327 * 0.9189 |
| = | -2.84 |
* 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 $313 Mil.
Revenue was 751.132 + 775.144 + 694.622 + 660.535 = $2,881 Mil.
Gross Profit was 149.877 + 163.893 + 154.815 + 130.347 = $599 Mil.
Total Current Assets was $649 Mil.
Total Assets was $2,584 Mil.
Property, Plant and Equipment(Net PPE) was $1,882 Mil.
Depreciation, Depletion and Amortization(DDA) was $179 Mil.
Selling, General, & Admin. Expense(SGA) was $68 Mil.
Total Current Liabilities was $322 Mil.
Long-Term Debt & Capital Lease Obligation was $103 Mil.
Net Income was 89.228 + 98.213 + 91.319 + 76.097 = $355 Mil.
Non Operating Income was 0.722 + -0.157 + 0.99 + 0.643 = $2 Mil.
Cash Flow from Operations was 161.677 + 124.863 + 172.135 + 119.27 = $578 Mil.
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Total Receivables was $314 Mil.
Revenue was 655.726 + 729.561 + 745.554 + 661.216 = $2,792 Mil.
Gross Profit was 123.253 + 160.719 + 176.209 + 130.782 = $591 Mil.
Total Current Assets was $531 Mil.
Total Assets was $2,175 Mil.
Property, Plant and Equipment(Net PPE) was $1,603 Mil.
Depreciation, Depletion and Amortization(DDA) was $157 Mil.
Selling, General, & Admin. Expense(SGA) was $57 Mil.
Total Current Liabilities was $274 Mil.
Long-Term Debt & Capital Lease Obligation was $115 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) |
| = | (312.747 / 2881.433) | / | (313.744 / 2792.057) |
| = | 0.108539 | / | 0.11237 |
| | = | 0.9659 |
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) |
| = | (590.963 / 2792.057) | / | (598.932 / 2881.433) |
| = | 0.211659 | / | 0.207859 |
| | = | 1.0183 |
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 - (648.694 + 1882.042) / 2583.565) | / | (1 - (530.886 + 1603.075) / 2174.71) |
| = | 0.020448 | / | 0.018738 |
| | = | 1.0913 |
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 |
| = | 2881.433 | / | 2792.057 |
| | = | 1.032 |
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)) |
| = | (157.203 / (157.203 + 1603.075)) | / | (178.845 / (178.845 + 1882.042)) |
| = | 0.089306 | / | 0.086781 |
| | = | 1.0291 |
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) |
| = | (67.984 / 2881.433) | / | (56.601 / 2792.057) |
| = | 0.023594 | / | 0.020272 |
| | = | 1.1639 |
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) |
| = | ((102.777 + 322.056) / 2583.565) | / | ((115.07 + 274.085) / 2174.71) |
| = | 0.164437 | / | 0.178946 |
| | = | 0.9189 |
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 |
| = | (354.857 - 2.198 | - | 577.945) | / | 2583.565 |
| | = | -0.0872 |
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.
Saia has a M-score of -2.84 suggests that the company is unlikely to be a manipulator.
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