Meere Co Beneish M-Score Historical Data
The historical data trend for Meere Co'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.
Meere Co Beneish M-Score Chart
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Meere Co Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-1.10 |
-2.90 |
-1.82 |
-2.24 |
-2.18 |
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Meere Co Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.24 |
-2.54 |
-2.99 |
-3.83 |
-2.18 |
Competitive Comparison of Meere Co's Beneish M-Score
For the Semiconductor Equipment & Materials subindustry, Meere Co'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.
Meere Co's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Meere Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Meere Co's Beneish M-Score falls into.
Meere Co 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 Meere Co 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 * 1.8971 | + | 0.528 * 1.1071 | + | 0.404 * 0.7256 | + | 0.892 * 0.6146 | + | 0.115 * 1.0031 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2586 | + | 4.679 * -0.013291 | - | 0.327 * 1.071 |
| = | -2.18 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩27,077 Mil.
Revenue was 19688.641 + 21286.413 + 19290.52 + 7013.075 = ₩67,279 Mil.
Gross Profit was 5615.54 + 6343.901 + 6211.155 + 461.097 = ₩18,632 Mil.
Total Current Assets was ₩91,242 Mil.
Total Assets was ₩149,199 Mil.
Property, Plant and Equipment(Net PPE) was ₩30,095 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,978 Mil.
Selling, General, & Admin. Expense(SGA) was ₩7,612 Mil.
Total Current Liabilities was ₩20,893 Mil.
Long-Term Debt & Capital Lease Obligation was ₩189 Mil.
Net Income was 2579.343 + -3503.901 + -1041.948 + -5175.484 = ₩-7,142 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 1483.237 + -3734.071 + -1566.588 + -1341.568 = ₩-5,159 Mil.
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Total Receivables was ₩23,225 Mil.
Revenue was 13663.792 + 43819.929 + 16791.806 + 35198.766 = ₩109,474 Mil.
Gross Profit was 2869.201 + 12309.572 + 5281.578 + 13104.329 = ₩33,565 Mil.
Total Current Assets was ₩84,612 Mil.
Total Assets was ₩155,295 Mil.
Property, Plant and Equipment(Net PPE) was ₩30,717 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,050 Mil.
Selling, General, & Admin. Expense(SGA) was ₩9,840 Mil.
Total Current Liabilities was ₩20,419 Mil.
Long-Term Debt & Capital Lease Obligation was ₩70 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) |
| = | (27077.321 / 67278.649) | / | (23224.708 / 109474.293) |
| = | 0.402465 | / | 0.212148 |
| | = | 1.8971 |
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) |
| = | (33564.68 / 109474.293) | / | (18631.693 / 67278.649) |
| = | 0.306599 | / | 0.276933 |
| | = | 1.1071 |
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 - (91242.346 + 30094.822) / 149198.686) | / | (1 - (84612.023 + 30717.114) / 155294.715) |
| = | 0.186741 | / | 0.257353 |
| | = | 0.7256 |
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 |
| = | 67278.649 | / | 109474.293 |
| | = | 0.6146 |
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)) |
| = | (3049.99 / (3049.99 + 30717.114)) | / | (2978.114 / (2978.114 + 30094.822)) |
| = | 0.090324 | / | 0.090047 |
| | = | 1.0031 |
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) |
| = | (7611.698 / 67278.649) | / | (9840.44 / 109474.293) |
| = | 0.113137 | / | 0.089888 |
| | = | 1.2586 |
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) |
| = | ((189.146 + 20893.455) / 149198.686) | / | ((70.246 + 20418.642) / 155294.715) |
| = | 0.141306 | / | 0.131936 |
| | = | 1.071 |
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 |
| = | (-7141.99 - 0 | - | -5158.99) | / | 149198.686 |
| | = | -0.013291 |
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.
Meere Co has a M-score of -2.18 suggests that the company is unlikely to be a manipulator.
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