BlueLinx Holdings Beneish M-Score Historical Data
The historical data trend for BlueLinx Holdings'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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BlueLinx Holdings Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.75 |
-2.02 |
-1.85 |
-2.99 |
-3.20 |
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BlueLinx Holdings 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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-2.99 |
-3.69 |
-3.67 |
-3.39 |
-3.20 |
Competitive Comparison
For the Industrial Distribution subindustry, BlueLinx Holdings'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.
BlueLinx Holdings Beneish M-Score Distribution
For the Industrial Distribution industry and Industrials sector, BlueLinx Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where BlueLinx Holdings's Beneish M-Score falls into.
BlueLinx Holdings 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 BlueLinx Holdings 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 * 1.2884 | + | 0.528 * 1.1139 | + | 0.404 * 0.9224 | + | 0.892 * 0.7048 | + | 0.115 * 0.9122 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3783 | + | 4.679 * -0.146288 | - | 0.327 * 0.981 |
| = | -3.20 |
* 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 $228 Mil.
Revenue was 712.529 + 809.981 + 815.967 + 797.904 = $3,136 Mil.
Gross Profit was 118.429 + 139.246 + 135.803 + 133.539 = $527 Mil.
Total Current Assets was $1,120 Mil.
Total Assets was $1,538 Mil.
Property, Plant and Equipment(Net PPE) was $263 Mil.
Depreciation, Depletion and Amortization(DDA) was $32 Mil.
Selling, General, & Admin. Expense(SGA) was $356 Mil.
Total Current Liabilities was $219 Mil.
Long-Term Debt & Capital Lease Obligation was $601 Mil.
Net Income was -18.124 + 24.382 + 24.466 + 17.812 = $49 Mil.
Non Operating Income was -31.035 + -0.594 + -0.594 + -0.594 = $-33 Mil.
Cash Flow from Operations was 75.561 + 77.606 + 64.153 + 88.965 = $306 Mil.
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Total Receivables was $252 Mil.
Revenue was 847.769 + 1060.761 + 1239.379 + 1302.305 = $4,450 Mil.
Gross Profit was 151.149 + 189.376 + 201.408 + 291.051 = $833 Mil.
Total Current Assets was $1,077 Mil.
Total Assets was $1,490 Mil.
Property, Plant and Equipment(Net PPE) was $251 Mil.
Depreciation, Depletion and Amortization(DDA) was $28 Mil.
Selling, General, & Admin. Expense(SGA) was $366 Mil.
Total Current Liabilities was $211 Mil.
Long-Term Debt & Capital Lease Obligation was $598 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) |
| = | (228.41 / 3136.381) | / | (251.555 / 4450.214) |
| = | 0.072826 | / | 0.056526 |
| | = | 1.2884 |
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) |
| = | (832.984 / 4450.214) | / | (527.017 / 3136.381) |
| = | 0.187178 | / | 0.168033 |
| | = | 1.1139 |
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 - (1120.399 + 263.214) / 1537.601) | / | (1 - (1076.932 + 251.326) / 1490.042) |
| = | 0.100148 | / | 0.108577 |
| | = | 0.9224 |
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 |
| = | 3136.381 | / | 4450.214 |
| | = | 0.7048 |
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)) |
| = | (27.613 / (27.613 + 251.326)) | / | (32.043 / (32.043 + 263.214)) |
| = | 0.098993 | / | 0.108526 |
| | = | 0.9122 |
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) |
| = | (355.819 / 3136.381) | / | (366.305 / 4450.214) |
| = | 0.113449 | / | 0.082312 |
| | = | 1.3783 |
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) |
| = | ((600.51 + 218.562) / 1537.601) | / | ((598.421 + 210.677) / 1490.042) |
| = | 0.532695 | / | 0.543003 |
| | = | 0.981 |
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 |
| = | (48.536 - -32.817 | - | 306.285) | / | 1537.601 |
| | = | -0.146288 |
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.
BlueLinx Holdings has a M-score of -3.20 suggests that the company is unlikely to be a manipulator.
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