Ciech Beneish M-Score Historical Data
The historical data trend for Ciech'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.
Ciech Beneish M-Score Chart
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Ciech Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-2.52 |
-3.06 |
-3.07 |
-2.99 |
-2.30 |
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Ciech Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.75 |
-2.30 |
-2.17 |
-2.43 |
-2.86 |
Competitive Comparison of Ciech's Beneish M-Score
For the Chemicals subindustry, Ciech'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.
Ciech's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Ciech's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ciech's Beneish M-Score falls into.
Ciech 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 Ciech 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 * 0.9556 | + | 0.528 * 0.9601 | + | 0.404 * 1.0873 | + | 0.892 * 1.1442 | + | 0.115 * 0.8939 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9503 | + | 4.679 * -0.099863 | - | 0.327 * 1.0427 |
| = | -2.86 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was zł714 Mil.
Revenue was 1161.124 + 1187.016 + 1730.224 + 1529.939 = zł5,608 Mil.
Gross Profit was 229.8 + 181.148 + 264.03 + 384.866 = zł1,060 Mil.
Total Current Assets was zł2,586 Mil.
Total Assets was zł7,494 Mil.
Property, Plant and Equipment(Net PPE) was zł4,075 Mil.
Depreciation, Depletion and Amortization(DDA) was zł480 Mil.
Selling, General, & Admin. Expense(SGA) was zł654 Mil.
Total Current Liabilities was zł2,953 Mil.
Long-Term Debt & Capital Lease Obligation was zł1,685 Mil.
Net Income was 51.53 + -73.878 + 57.394 + 332.482 = zł368 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = zł0 Mil.
Cash Flow from Operations was 289.736 + 523.275 + -20.042 + 322.925 = zł1,116 Mil.
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Total Receivables was zł653 Mil.
Revenue was 1406.667 + 1236.289 + 1242.564 + 1015.863 = zł4,901 Mil.
Gross Profit was 255.716 + 259.314 + 268.333 + 105.978 = zł889 Mil.
Total Current Assets was zł2,780 Mil.
Total Assets was zł7,708 Mil.
Property, Plant and Equipment(Net PPE) was zł4,139 Mil.
Depreciation, Depletion and Amortization(DDA) was zł431 Mil.
Selling, General, & Admin. Expense(SGA) was zł602 Mil.
Total Current Liabilities was zł2,699 Mil.
Long-Term Debt & Capital Lease Obligation was zł1,876 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) |
| = | (714.46 / 5608.303) | / | (653.431 / 4901.383) |
| = | 0.127393 | / | 0.133316 |
| | = | 0.9556 |
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) |
| = | (889.341 / 4901.383) | / | (1059.844 / 5608.303) |
| = | 0.181447 | / | 0.188978 |
| | = | 0.9601 |
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 - (2586.039 + 4074.514) / 7493.91) | / | (1 - (2780.244 + 4139.082) / 7707.606) |
| = | 0.111205 | / | 0.102273 |
| | = | 1.0873 |
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 |
| = | 5608.303 | / | 4901.383 |
| | = | 1.1442 |
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)) |
| = | (430.575 / (430.575 + 4139.082)) | / | (480.088 / (480.088 + 4074.514)) |
| = | 0.094225 | / | 0.105407 |
| | = | 0.8939 |
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) |
| = | (654.072 / 5608.303) | / | (601.545 / 4901.383) |
| = | 0.116626 | / | 0.12273 |
| | = | 0.9503 |
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) |
| = | ((1685.031 + 2953.243) / 7493.91) | / | ((1876.304 + 2698.733) / 7707.606) |
| = | 0.618939 | / | 0.593574 |
| | = | 1.0427 |
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 |
| = | (367.528 - 0 | - | 1115.894) | / | 7493.91 |
| | = | -0.099863 |
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.
Ciech has a M-score of -2.86 suggests that the company is unlikely to be a manipulator.
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