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 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.94 |
-2.50 |
-1.92 |
-2.70 |
-3.09 |
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UFP Industries 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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-2.70 |
-3.10 |
-3.23 |
-3.15 |
-3.09 |
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 * 1.1863 | + | 0.528 * 0.9456 | + | 0.404 * 0.9466 | + | 0.892 * 0.7498 | + | 0.115 * 0.9577 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2288 | + | 4.679 * -0.110312 | - | 0.327 * 0.8331 |
| = | -3.09 |
* 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 $579 Mil.
Revenue was 1524.353 + 1827.637 + 2043.918 + 1822.476 = $7,218 Mil.
Gross Profit was 296.142 + 364.4 + 400.067 + 358.329 = $1,419 Mil.
Total Current Assets was $2,502 Mil.
Total Assets was $4,018 Mil.
Property, Plant and Equipment(Net PPE) was $880 Mil.
Depreciation, Depletion and Amortization(DDA) was $132 Mil.
Selling, General, & Admin. Expense(SGA) was $767 Mil.
Total Current Liabilities was $568 Mil.
Long-Term Debt & Capital Lease Obligation was $318 Mil.
Net Income was 103.447 + 134.035 + 150.761 + 126.069 = $514 Mil.
Non Operating Income was 3.87 + -1.427 + -2.284 + -2.526 = $-2 Mil.
Cash Flow from Operations was 248.087 + 390.739 + 358.14 + -37.076 = $960 Mil.
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Total Receivables was $651 Mil.
Revenue was 1913.697 + 2322.855 + 2900.874 + 2489.313 = $9,627 Mil.
Gross Profit was 357.47 + 450.176 + 503.452 + 478.363 = $1,789 Mil.
Total Current Assets was $2,262 Mil.
Total Assets was $3,672 Mil.
Property, Plant and Equipment(Net PPE) was $796 Mil.
Depreciation, Depletion and Amortization(DDA) was $114 Mil.
Selling, General, & Admin. Expense(SGA) was $832 Mil.
Total Current Liabilities was $612 Mil.
Long-Term Debt & Capital Lease Obligation was $361 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) |
| = | (578.826 / 7218.384) | / | (650.73 / 9626.739) |
| = | 0.080188 | / | 0.067596 |
| | = | 1.1863 |
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) |
| = | (1789.461 / 9626.739) | / | (1418.938 / 7218.384) |
| = | 0.185884 | / | 0.196573 |
| | = | 0.9456 |
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 - (2502.089 + 880.351) / 4017.797) | / | (1 - (2262.113 + 796.499) / 3672.073) |
| = | 0.158136 | / | 0.167061 |
| | = | 0.9466 |
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 |
| = | 7218.384 | / | 9626.739 |
| | = | 0.7498 |
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)) |
| = | (113.562 / (113.562 + 796.499)) | / | (131.89 / (131.89 + 880.351)) |
| = | 0.124785 | / | 0.130295 |
| | = | 0.9577 |
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) |
| = | (766.633 / 7218.384) | / | (832.079 / 9626.739) |
| = | 0.106206 | / | 0.086434 |
| | = | 1.2288 |
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) |
| = | ((318.419 + 567.976) / 4017.797) | / | ((360.573 + 611.835) / 3672.073) |
| = | 0.220617 | / | 0.264812 |
| | = | 0.8331 |
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 |
| = | (514.312 - -2.367 | - | 959.89) | / | 4017.797 |
| | = | -0.110312 |
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 -3.09 suggests that the company is unlikely to be a manipulator.
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