Veritiv Beneish M-Score Historical Data
The historical data trend for Veritiv'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.
Veritiv Beneish M-Score Chart
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Veritiv Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-2.45 |
-3.04 |
-3.00 |
-2.33 |
-2.45 |
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Veritiv Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.34 |
-2.45 |
-2.64 |
-2.81 |
-2.86 |
Competitive Comparison of Veritiv's Beneish M-Score
For the Conglomerates subindustry, Veritiv'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.
Veritiv's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, Veritiv's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Veritiv's Beneish M-Score falls into.
Veritiv 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 Veritiv 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 * 0.9487 | + | 0.528 * 0.9147 | + | 0.404 * 1.1008 | + | 0.892 * 0.8291 | + | 0.115 * 1.1144 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.084 | + | 4.679 * -0.059938 | - | 0.327 * 0.6892 |
| = | -2.86 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was $757 Mil.
Revenue was 1461 + 1457.3 + 1510.2 + 1663.4 = $6,092 Mil.
Gross Profit was 362.7 + 360.7 + 366.1 + 392 = $1,482 Mil.
Total Current Assets was $1,354 Mil.
Total Assets was $1,995 Mil.
Property, Plant and Equipment(Net PPE) was $128 Mil.
Depreciation, Depletion and Amortization(DDA) was $40 Mil.
Selling, General, & Admin. Expense(SGA) was $1,066 Mil.
Total Current Liabilities was $669 Mil.
Long-Term Debt & Capital Lease Obligation was $61 Mil.
Net Income was 60.8 + 70.7 + 68.7 + 71.6 = $272 Mil.
Non Operating Income was 1.9 + 1.9 + -1 + 5.8 = $9 Mil.
Cash Flow from Operations was 124 + 94.4 + 70.9 + 93.5 = $383 Mil.
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Total Receivables was $962 Mil.
Revenue was 1804.1 + 1820.7 + 1858.1 + 1864.8 = $7,348 Mil.
Gross Profit was 415.8 + 409.8 + 402.7 + 406.1 = $1,634 Mil.
Total Current Assets was $1,584 Mil.
Total Assets was $2,240 Mil.
Property, Plant and Equipment(Net PPE) was $131 Mil.
Depreciation, Depletion and Amortization(DDA) was $48 Mil.
Selling, General, & Admin. Expense(SGA) was $1,187 Mil.
Total Current Liabilities was $800 Mil.
Long-Term Debt & Capital Lease Obligation was $390 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) |
| = | (756.9 / 6091.9) | / | (962.3 / 7347.7) |
| = | 0.124247 | / | 0.130966 |
| | = | 0.9487 |
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) |
| = | (1634.4 / 7347.7) | / | (1481.5 / 6091.9) |
| = | 0.222437 | / | 0.243192 |
| | = | 0.9147 |
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 - (1353.6 + 127.6) / 1995.4) | / | (1 - (1584 + 131.3) / 2239.6) |
| = | 0.257693 | / | 0.234104 |
| | = | 1.1008 |
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 |
| = | 6091.9 | / | 7347.7 |
| | = | 0.8291 |
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)) |
| = | (47.7 / (47.7 + 131.3)) | / | (40.1 / (40.1 + 127.6)) |
| = | 0.26648 | / | 0.239117 |
| | = | 1.1144 |
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) |
| = | (1066.3 / 6091.9) | / | (1186.5 / 7347.7) |
| = | 0.175036 | / | 0.161479 |
| | = | 1.084 |
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) |
| = | ((61.2 + 669.2) / 1995.4) | / | ((389.9 + 799.6) / 2239.6) |
| = | 0.366042 | / | 0.531122 |
| | = | 0.6892 |
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 |
| = | (271.8 - 8.6 | - | 382.8) | / | 1995.4 |
| | = | -0.059938 |
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.
Veritiv has a M-score of -2.86 suggests that the company is unlikely to be a manipulator.
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