Marel hf Beneish M-Score Historical Data
The historical data trend for Marel hf'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.
Marel hf Beneish M-Score Chart
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Marel hf Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.46 |
-2.46 |
-2.68 |
-2.37 |
-2.78 |
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Marel hf Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.30 |
-2.41 |
-2.57 |
-2.78 |
-2.85 |
Competitive Comparison of Marel hf's Beneish M-Score
For the Specialty Industrial Machinery subindustry, Marel hf'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.
Marel hf's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Marel hf's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Marel hf's Beneish M-Score falls into.
Marel hf 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 Marel hf 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 * 0.8388 | + | 0.528 * 0.9536 | + | 0.404 * 1.054 | + | 0.892 * 0.9796 | + | 0.115 * 0.9298 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0446 | + | 4.679 * -0.042526 | - | 0.327 * 0.9494 |
| = | -2.85 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was kr50,399 Mil.
Revenue was 61981.417 + 67519.432 + 59529.423 + 63247.347 = kr252,278 Mil.
Gross Profit was 22307.902 + 23842.8 + 21106.691 + 21322.022 = kr88,579 Mil.
Total Current Assets was kr109,061 Mil.
Total Assets was kr384,868 Mil.
Property, Plant and Equipment(Net PPE) was kr57,685 Mil.
Depreciation, Depletion and Amortization(DDA) was kr14,453 Mil.
Selling, General, & Admin. Expense(SGA) was kr57,911 Mil.
Total Current Liabilities was kr89,277 Mil.
Long-Term Debt & Capital Lease Obligation was kr124,819 Mil.
Net Income was -480.709 + 1311.203 + 1489.711 + 464.173 = kr2,784 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = kr0 Mil.
Cash Flow from Operations was 976.44 + 12765.393 + 4675.626 + 733.693 = kr19,151 Mil.
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Total Receivables was kr61,334 Mil.
Revenue was 66201.71 + 71620.04 + 61658.069 + 58042.69 = kr257,523 Mil.
Gross Profit was 22594.996 + 24024.629 + 20347.436 + 19255.038 = kr86,222 Mil.
Total Current Assets was kr130,021 Mil.
Total Assets was kr401,620 Mil.
Property, Plant and Equipment(Net PPE) was kr55,637 Mil.
Depreciation, Depletion and Amortization(DDA) was kr12,737 Mil.
Selling, General, & Admin. Expense(SGA) was kr56,589 Mil.
Total Current Liabilities was kr122,090 Mil.
Long-Term Debt & Capital Lease Obligation was kr113,241 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) |
| = | (50399.334 / 252277.619) | / | (61333.502 / 257522.509) |
| = | 0.199777 | / | 0.238168 |
| | = | 0.8388 |
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) |
| = | (86222.099 / 257522.509) | / | (88579.415 / 252277.619) |
| = | 0.334814 | / | 0.351119 |
| | = | 0.9536 |
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 - (109060.855 + 57685.08) / 384867.645) | / | (1 - (130021.105 + 55636.663) / 401619.761) |
| = | 0.566745 | / | 0.537728 |
| | = | 1.054 |
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 |
| = | 252277.619 | / | 257522.509 |
| | = | 0.9796 |
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)) |
| = | (12736.652 / (12736.652 + 55636.663)) | / | (14452.83 / (14452.83 + 57685.08)) |
| = | 0.186281 | / | 0.20035 |
| | = | 0.9298 |
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) |
| = | (57911.188 / 252277.619) | / | (56588.9 / 257522.509) |
| = | 0.229553 | / | 0.219744 |
| | = | 1.0446 |
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) |
| = | ((124819.097 + 89276.675) / 384867.645) | / | ((113241.325 + 122089.922) / 401619.761) |
| = | 0.556284 | / | 0.585955 |
| | = | 0.9494 |
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 |
| = | (2784.378 - 0 | - | 19151.152) | / | 384867.645 |
| | = | -0.042526 |
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.
Marel hf has a M-score of -2.85 suggests that the company is unlikely to be a manipulator.
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