UFP Industries Beneish M-Score Historical Data
The historical data trend for UFP Industries'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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UFP Industries Annual Data
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Trend |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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|
|
|
|
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-2.38 |
-2.33 |
-2.94 |
-2.50 |
-1.92 |
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UFP Industries Quarterly Data
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Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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|
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-1.35 |
-1.91 |
-1.92 |
-2.00 |
-2.50 |
Competitive Comparison
For the Lumber & Wood Production subindustry, UFP Industries'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.
UFP Industries Beneish M-Score Distribution
For the Forest Products industry and Basic Materials sector, UFP Industries's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where UFP Industries's Beneish M-Score falls into.
UFP Industries 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 UFP Industries 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 * 0.8423 | + | 0.528 * 0.867 | + | 0.404 * 0.9437 | + | 0.892 * 1.2829 | + | 0.115 * 0.9326 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0965 | + | 4.679 * -0.0174 | - | 0.327 * 0.7679 |
| = | -2.50 |
* 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 (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $1,060 Mil.
Revenue was 2900.874 + 2489.313 + 2016.805 + 2093.784 = $9,501 Mil.
Gross Profit was 503.452 + 478.363 + 371.564 + 327.555 = $1,681 Mil.
Total Current Assets was $2,376 Mil.
Total Assets was $3,611 Mil.
Property, Plant and Equipment(Net PPE) was $733 Mil.
Depreciation, Depletion and Amortization(DDA) was $105 Mil.
Selling, General, & Admin. Expense(SGA) was $782 Mil.
Total Current Liabilities was $824 Mil.
Long-Term Debt & Capital Lease Obligation was $363 Mil.
Net Income was 203.118 + 189.703 + 137.906 + 121.041 = $652 Mil.
Non Operating Income was -1.017 + -0.515 + -1.491 + -0.946 = $-4 Mil.
Cash Flow from Operations was 335.428 + -245.031 + 230.714 + 397.496 = $719 Mil.
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Total Receivables was $981 Mil.
Revenue was 2700.541 + 1825.004 + 1393.708 + 1486.227 = $7,405 Mil.
Gross Profit was 421.294 + 286.554 + 187.055 + 241.074 = $1,136 Mil.
Total Current Assets was $2,123 Mil.
Total Assets was $3,228 Mil.
Property, Plant and Equipment(Net PPE) was $631 Mil.
Depreciation, Depletion and Amortization(DDA) was $84 Mil.
Selling, General, & Admin. Expense(SGA) was $556 Mil.
Total Current Liabilities was $731 Mil.
Long-Term Debt & Capital Lease Obligation was $650 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) |
| = | (1059.626 / 9500.776) | / | (980.571 / 7405.48) |
| = | 0.11153047 | / | 0.13241154 |
| | = | 0.8423 |
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) |
| = | (1135.977 / 7405.48) | / | (1680.934 / 9500.776) |
| = | 0.15339681 | / | 0.17692597 |
| | = | 0.867 |
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 - (2376.444 + 732.989) / 3610.823) | / | (1 - (2122.5 + 630.784) / 3228.283) |
| = | 0.13885754 | / | 0.14713673 |
| | = | 0.9437 |
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 |
| = | 9500.776 | / | 7405.48 |
| | = | 1.2829 |
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)) |
| = | (83.756 / (83.756 + 630.784)) | / | (105.371 / (105.371 + 732.989)) |
| = | 0.11721667 | / | 0.12568706 |
| | = | 0.9326 |
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) |
| = | (782.304 / 9500.776) | / | (556.112 / 7405.48) |
| = | 0.08234106 | / | 0.07509466 |
| | = | 1.0965 |
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) |
| = | ((362.779 + 823.993) / 3610.823) | / | ((650.42 + 731.317) / 3228.283) |
| = | 0.32867078 | / | 0.42800987 |
| | = | 0.7679 |
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 |
| = | (651.768 - -3.969 | - | 718.607) | / | 3610.823 |
| | = | -0.0174 |
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.
UFP Industries has a M-score of -2.50 suggests that the company is unlikely to be a manipulator.
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