Orlen Beneish M-Score Historical Data
The historical data trend for Orlen'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.
Orlen Beneish M-Score Chart
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Orlen Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.92 |
-2.72 |
-2.17 |
-1.03 |
-2.61 |
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Orlen 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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-1.33 |
-1.45 |
-2.12 |
-2.61 |
-2.82 |
Competitive Comparison of Orlen's Beneish M-Score
For the Oil & Gas Integrated subindustry, Orlen'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.
Orlen's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Orlen's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Orlen's Beneish M-Score falls into.
Orlen 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 Orlen 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 * 1.2155 | + | 0.404 * 0.9827 | + | 0.892 * 0.9774 | + | 0.115 * 0.8259 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3462 | + | 4.679 * -0.0594 | - | 0.327 * 0.8326 |
| = | -2.82 |
* 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 $9,705 Mil.
Revenue was 20518.49 + 28024.89 + 18796.903 + 18596.782 = $85,937 Mil.
Gross Profit was 2614.53 + 5423.947 + 2949.975 + 2515.591 = $13,504 Mil.
Total Current Assets was $21,571 Mil.
Total Assets was $65,543 Mil.
Property, Plant and Equipment(Net PPE) was $37,674 Mil.
Depreciation, Depletion and Amortization(DDA) was $3,629 Mil.
Selling, General, & Admin. Expense(SGA) was $5,470 Mil.
Total Current Liabilities was $16,572 Mil.
Long-Term Debt & Capital Lease Obligation was $5,128 Mil.
Net Income was 689.084 + 913.129 + 863.286 + 1143.904 = $3,609 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 2908.356 + 1037.239 + 1804.576 + 1752.49 = $7,503 Mil.
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Total Receivables was $11,481 Mil.
Revenue was 28866.245 + 26479 + 18171.618 + 14405.708 = $87,923 Mil.
Gross Profit was 4794.177 + 5759.392 + 2955.209 + 3285.171 = $16,794 Mil.
Total Current Assets was $30,412 Mil.
Total Assets was $69,532 Mil.
Property, Plant and Equipment(Net PPE) was $32,321 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,529 Mil.
Selling, General, & Admin. Expense(SGA) was $4,157 Mil.
Total Current Liabilities was $23,044 Mil.
Long-Term Debt & Capital Lease Obligation was $4,605 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) |
| = | (9705.237 / 85937.065) | / | (11481.402 / 87922.571) |
| = | 0.112934 | / | 0.130585 |
| | = | 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) |
| = | (16793.949 / 87922.571) | / | (13504.043 / 85937.065) |
| = | 0.191008 | / | 0.157139 |
| | = | 1.2155 |
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 - (21570.931 + 37673.804) / 65543.182) | / | (1 - (30411.885 + 32321.132) / 69532.39) |
| = | 0.096096 | / | 0.097787 |
| | = | 0.9827 |
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 |
| = | 85937.065 | / | 87922.571 |
| | = | 0.9774 |
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)) |
| = | (2528.549 / (2528.549 + 32321.132)) | / | (3628.592 / (3628.592 + 37673.804)) |
| = | 0.072556 | / | 0.087854 |
| | = | 0.8259 |
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) |
| = | (5470.301 / 85937.065) | / | (4157.429 / 87922.571) |
| = | 0.063655 | / | 0.047285 |
| | = | 1.3462 |
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) |
| = | ((5128.376 + 16571.898) / 65543.182) | / | ((4604.773 + 23044.05) / 69532.39) |
| = | 0.331084 | / | 0.397639 |
| | = | 0.8326 |
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 |
| = | (3609.403 - 0 | - | 7502.661) | / | 65543.182 |
| | = | -0.0594 |
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.
Orlen has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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