Knoll Beneish M-Score Historical Data
The historical data trend for Knoll'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.
Knoll Beneish M-Score Chart
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Knoll Annual Data
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Trend |
Dec11 |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
| Beneish M-Score |
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-2.82 |
-2.60 |
-2.24 |
-2.73 |
-2.71 |
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Knoll Quarterly Data
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Jun16 |
Sep16 |
Dec16 |
Mar17 |
Jun17 |
Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
| Beneish M-Score |
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-2.54 |
-2.67 |
-2.61 |
-2.71 |
-2.89 |
Competitive Comparison of Knoll's Beneish M-Score
For the Business Equipment & Supplies subindustry, Knoll'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.
Knoll's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Knoll's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Knoll's Beneish M-Score falls into.
Knoll 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 Knoll 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 * 0.8403 | + | 0.528 * 1.064 | + | 0.404 * 1.0475 | + | 0.892 * 0.8086 | + | 0.115 * 1.1776 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0641 | + | 4.679 * -0.038862 | - | 0.327 * 0.7693 |
| = | -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 (Mar21) TTM: | Last Year (Mar20) TTM: |
Total Receivables was $78 Mil.
Revenue was 264.2 + 312.9 + 309.4 + 274.1 = $1,161 Mil.
Gross Profit was 95.7 + 111.3 + 113.4 + 95.7 = $416 Mil.
Total Current Assets was $348 Mil.
Total Assets was $1,451 Mil.
Property, Plant and Equipment(Net PPE) was $419 Mil.
Depreciation, Depletion and Amortization(DDA) was $43 Mil.
Selling, General, & Admin. Expense(SGA) was $362 Mil.
Total Current Liabilities was $276 Mil.
Long-Term Debt & Capital Lease Obligation was $442 Mil.
Net Income was -1.9 + -0.6 + 7 + -9.6 = $-5 Mil.
Non Operating Income was -4.6 + -9.4 + -4.3 + -22.1 = $-40 Mil.
Cash Flow from Operations was 14.6 + 41.3 + 29.9 + 5.9 = $92 Mil.
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Total Receivables was $114 Mil.
Revenue was 340 + 371.5 + 356.5 + 367.3 = $1,435 Mil.
Gross Profit was 122.3 + 144.1 + 140.4 + 140.7 = $548 Mil.
Total Current Assets was $491 Mil.
Total Assets was $1,496 Mil.
Property, Plant and Equipment(Net PPE) was $332 Mil.
Depreciation, Depletion and Amortization(DDA) was $41 Mil.
Selling, General, & Admin. Expense(SGA) was $421 Mil.
Total Current Liabilities was $275 Mil.
Long-Term Debt & Capital Lease Obligation was $688 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) |
| = | (77.6 / 1160.6) | / | (114.2 / 1435.3) |
| = | 0.066862 | / | 0.079565 |
| | = | 0.8403 |
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) |
| = | (547.5 / 1435.3) | / | (416.1 / 1160.6) |
| = | 0.381453 | / | 0.358521 |
| | = | 1.064 |
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 - (348 + 418.7) / 1451.3) | / | (1 - (490.5 + 332) / 1496.3) |
| = | 0.471715 | / | 0.450311 |
| | = | 1.0475 |
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 |
| = | 1160.6 | / | 1435.3 |
| | = | 0.8086 |
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)) |
| = | (40.8 / (40.8 + 332)) | / | (42.9 / (42.9 + 418.7)) |
| = | 0.109442 | / | 0.092938 |
| | = | 1.1776 |
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) |
| = | (362 / 1160.6) | / | (420.7 / 1435.3) |
| = | 0.311908 | / | 0.293109 |
| | = | 1.0641 |
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) |
| = | ((442.4 + 276) / 1451.3) | / | ((688 + 274.8) / 1496.3) |
| = | 0.495004 | / | 0.643454 |
| | = | 0.7693 |
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 |
| = | (-5.1 - -40.4 | - | 91.7) | / | 1451.3 |
| | = | -0.038862 |
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.
Knoll has a M-score of -2.84 suggests that the company is unlikely to be a manipulator.
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