AmoreG Beneish M-Score Historical Data
The historical data trend for AmoreG'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.
AmoreG Beneish M-Score Chart
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AmoreG Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.94 |
-2.97 |
-2.71 |
-2.26 |
-2.65 |
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AmoreG Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.26 |
-2.61 |
-2.69 |
-2.55 |
-2.65 |
Competitive Comparison of AmoreG's Beneish M-Score
For the Household & Personal Products subindustry, AmoreG'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.
AmoreG's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, AmoreG's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AmoreG's Beneish M-Score falls into.
AmoreG 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 AmoreG 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 * 1.1069 | + | 0.528 * 0.9859 | + | 0.404 * 0.9432 | + | 0.892 * 0.8946 | + | 0.115 * 1.1917 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.023 | + | 4.679 * -0.035402 | - | 0.327 * 0.9939 |
| = | -2.65 |
* 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 ₩362,632 Mil.
Revenue was 1018005.573 + 963348.466 + 1030839.084 + 1009149.916 = ₩4,021,343 Mil.
Gross Profit was 731336.955 + 691579.002 + 731206.089 + 701643.427 = ₩2,855,765 Mil.
Total Current Assets was ₩2,750,249 Mil.
Total Assets was ₩7,631,431 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,860,385 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩259,187 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,699,716 Mil.
Total Current Liabilities was ₩856,205 Mil.
Long-Term Debt & Capital Lease Obligation was ₩43,537 Mil.
Net Income was 18307.952 + 25066.37 + 22501.608 + 53425.69 = ₩119,302 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 145067.971 + -38573.29 + 154865.576 + 128112.449 = ₩389,473 Mil.
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Total Receivables was ₩366,191 Mil.
Revenue was 1183938.506 + 1021790.04 + 1026391.134 + 1262837.127 = ₩4,494,957 Mil.
Gross Profit was 842524.328 + 705829.117 + 708483.785 + 890332.996 = ₩3,147,170 Mil.
Total Current Assets was ₩2,566,384 Mil.
Total Assets was ₩7,651,004 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,936,543 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩322,705 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,857,223 Mil.
Total Current Liabilities was ₩851,902 Mil.
Long-Term Debt & Capital Lease Obligation was ₩55,663 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) |
| = | (362631.759 / 4021343.039) | / | (366190.882 / 4494956.807) |
| = | 0.090177 | / | 0.081467 |
| | = | 1.1069 |
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) |
| = | (3147170.226 / 4494956.807) | / | (2855765.473 / 4021343.039) |
| = | 0.700156 | / | 0.710152 |
| | = | 0.9859 |
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 - (2750248.647 + 2860385.117) / 7631430.778) | / | (1 - (2566383.547 + 2936543.3) / 7651003.801) |
| = | 0.264799 | / | 0.280758 |
| | = | 0.9432 |
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 |
| = | 4021343.039 | / | 4494956.807 |
| | = | 0.8946 |
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)) |
| = | (322705 / (322705 + 2936543.3)) | / | (259187 / (259187 + 2860385.117)) |
| = | 0.099012 | / | 0.083084 |
| | = | 1.1917 |
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) |
| = | (1699715.599 / 4021343.039) | / | (1857222.895 / 4494956.807) |
| = | 0.422674 | / | 0.413179 |
| | = | 1.023 |
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) |
| = | ((43536.732 + 856205.499) / 7631430.778) | / | ((55663.299 + 851901.945) / 7651003.801) |
| = | 0.1179 | / | 0.11862 |
| | = | 0.9939 |
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 |
| = | (119301.62 - 0 | - | 389472.706) | / | 7631430.778 |
| | = | -0.035402 |
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.
AmoreG has a M-score of -2.65 suggests that the company is unlikely to be a manipulator.
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