UPM-Kymmene Oyj Beneish M-Score Historical Data
The historical data trend for UPM-Kymmene Oyj'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.
UPM-Kymmene Oyj Beneish M-Score Chart
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UPM-Kymmene Oyj Annual Data
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Dec14 |
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Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.98 |
-2.71 |
-2.40 |
-2.14 |
-3.02 |
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UPM-Kymmene Oyj Quarterly Data
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Dec19 |
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Sep24 |
| Beneish M-Score |
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-3.02 |
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Competitive Comparison of UPM-Kymmene Oyj's Beneish M-Score
For the Paper & Paper Products subindustry, UPM-Kymmene Oyj'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.
UPM-Kymmene Oyj's Beneish M-Score Distribution in the Forest Products Industry
For the Forest Products industry and Basic Materials sector, UPM-Kymmene Oyj's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where UPM-Kymmene Oyj's Beneish M-Score falls into.
UPM-Kymmene Oyj 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 UPM-Kymmene Oyj 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 * 0.8648 | + | 0.528 * 1.2475 | + | 0.404 * 0.9868 | + | 0.892 * 0.8925 | + | 0.115 * 0.7368 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9917 | + | 4.679 * -0.101824 | - | 0.327 * 0.826 |
| = | -3.02 |
* 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 €1,309 Mil.
Revenue was €10,460 Mil.
Gross Profit was €3,070 Mil.
Total Current Assets was €4,559 Mil.
Total Assets was €18,473 Mil.
Property, Plant and Equipment(Net PPE) was €7,736 Mil.
Depreciation, Depletion and Amortization(DDA) was €660 Mil.
Selling, General, & Admin. Expense(SGA) was €886 Mil.
Total Current Liabilities was €2,441 Mil.
Long-Term Debt & Capital Lease Obligation was €2,962 Mil.
Net Income was €388 Mil.
Gross Profit was €0 Mil.
Cash Flow from Operations was €2,269 Mil.
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Total Receivables was €1,696 Mil.
Revenue was €11,720 Mil.
Gross Profit was €4,291 Mil.
Total Current Assets was €7,232 Mil.
Total Assets was €22,207 Mil.
Property, Plant and Equipment(Net PPE) was €7,449 Mil.
Depreciation, Depletion and Amortization(DDA) was €458 Mil.
Selling, General, & Admin. Expense(SGA) was €1,001 Mil.
Total Current Liabilities was €3,523 Mil.
Long-Term Debt & Capital Lease Obligation was €4,340 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) |
| = | (1309 / 10460) | / | (1696 / 11720) |
| = | 0.125143 | / | 0.14471 |
| | = | 0.8648 |
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) |
| = | (4291 / 11720) | / | (3070 / 10460) |
| = | 0.366126 | / | 0.293499 |
| | = | 1.2475 |
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 - (4559 + 7736) / 18473) | / | (1 - (7232 + 7449) / 22207) |
| = | 0.334434 | / | 0.338902 |
| | = | 0.9868 |
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 |
| = | 10460 | / | 11720 |
| | = | 0.8925 |
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)) |
| = | (458 / (458 + 7449)) | / | (660 / (660 + 7736)) |
| = | 0.057923 | / | 0.078609 |
| | = | 0.7368 |
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) |
| = | (886 / 10460) | / | (1001 / 11720) |
| = | 0.084704 | / | 0.08541 |
| | = | 0.9917 |
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) |
| = | ((2962 + 2441) / 18473) | / | ((4340 + 3523) / 22207) |
| = | 0.292481 | / | 0.354078 |
| | = | 0.826 |
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 |
| = | (388 - 0 | - | 2269) | / | 18473 |
| | = | -0.101824 |
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.
UPM-Kymmene Oyj has a M-score of -3.02 suggests that the company is unlikely to be a manipulator.
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