SuNAM Co Beneish M-Score Historical Data
The historical data trend for SuNAM 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.
SuNAM Co Beneish M-Score Chart
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SuNAM Co Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
-1.59 |
8.07 |
27.22 |
-5.96 |
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SuNAM Co Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
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Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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10.44 |
-2.97 |
-4.38 |
-5.96 |
-7.17 |
Competitive Comparison of SuNAM Co's Beneish M-Score
For the Semiconductor Equipment & Materials subindustry, SuNAM 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.
SuNAM Co's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, SuNAM Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where SuNAM Co's Beneish M-Score falls into.
SuNAM 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 SuNAM 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 * 0.4972 | + | 0.528 * -0.0684 | + | 0.404 * 0.2382 | + | 0.892 * 0.8733 | + | 0.115 * 1.1055 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4743 | + | 4.679 * -0.716394 | - | 0.327 * 0.4652 |
| = | -7.17 |
* 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 ₩530 Mil.
Revenue was 415.272 + 292.463 + 1892.151 + 2793.249 = ₩5,393 Mil.
Gross Profit was 51.649 + -212.981 + -274.121 + 718.548 = ₩283 Mil.
Total Current Assets was ₩5,755 Mil.
Total Assets was ₩14,477 Mil.
Property, Plant and Equipment(Net PPE) was ₩8,329 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩717 Mil.
Selling, General, & Admin. Expense(SGA) was ₩652 Mil.
Total Current Liabilities was ₩3,321 Mil.
Long-Term Debt & Capital Lease Obligation was ₩23 Mil.
Net Income was -860.407 + -1285.29 + -7094.215 + -2804.509 = ₩-12,044 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 178.71 + 226.927 + -3072.012 + 992.925 = ₩-1,673 Mil.
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Total Receivables was ₩1,221 Mil.
Revenue was 1413.049 + 1130.635 + 1234.618 + 2397.53 = ₩6,176 Mil.
Gross Profit was 591.449 + -144.243 + -779.876 + 310.503 = ₩-22 Mil.
Total Current Assets was ₩8,412 Mil.
Total Assets was ₩17,360 Mil.
Property, Plant and Equipment(Net PPE) was ₩6,974 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩670 Mil.
Selling, General, & Admin. Expense(SGA) was ₩506 Mil.
Total Current Liabilities was ₩8,572 Mil.
Long-Term Debt & Capital Lease Obligation was ₩47 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) |
| = | (529.965 / 5393.135) | / | (1220.529 / 6175.832) |
| = | 0.098267 | / | 0.19763 |
| | = | 0.4972 |
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) |
| = | (-22.167 / 6175.832) | / | (283.095 / 5393.135) |
| = | -0.003589 | / | 0.052492 |
| | = | -0.0684 |
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 - (5755.325 + 8329.282) / 14476.628) | / | (1 - (8411.93 + 6973.768) / 17359.646) |
| = | 0.02708 | / | 0.113709 |
| | = | 0.2382 |
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 |
| = | 5393.135 | / | 6175.832 |
| | = | 0.8733 |
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)) |
| = | (669.831 / (669.831 + 6973.768)) | / | (717.108 / (717.108 + 8329.282)) |
| = | 0.087633 | / | 0.07927 |
| | = | 1.1055 |
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) |
| = | (652.026 / 5393.135) | / | (506.457 / 6175.832) |
| = | 0.120899 | / | 0.082006 |
| | = | 1.4743 |
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) |
| = | ((22.75 + 3320.797) / 14476.628) | / | ((46.98 + 8571.959) / 17359.646) |
| = | 0.230962 | / | 0.496493 |
| | = | 0.4652 |
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 |
| = | (-12044.421 - 0 | - | -1673.45) | / | 14476.628 |
| | = | -0.716394 |
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.
SuNAM Co has a M-score of -7.17 suggests that the company is unlikely to be a manipulator.
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