SK Square Beneish M-Score Historical Data
The historical data trend for SK Square'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.
SK Square Beneish M-Score Chart
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SK Square Annual Data
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Trend |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
2.03 |
-1.39 |
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SK Square Quarterly Data
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|
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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2.03 |
-1.28 |
-0.30 |
4.87 |
-1.39 |
Competitive Comparison of SK Square's Beneish M-Score
For the Semiconductors subindustry, SK Square'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.
SK Square's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, SK Square's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where SK Square's Beneish M-Score falls into.
SK Square 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 SK Square 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 * 0.9391 | + | 0.528 * 0.0781 | + | 0.404 * 1.0114 | + | 0.892 * 1.8062 | + | 0.115 * 0.9819 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.4511 | + | 4.679 * 0.160759 | - | 0.327 * 0.81 |
| = | -1.39 |
* 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 ₩1,019,074 Mil.
Revenue was 2301420 + 1658157 + 468566 + 885673 = ₩5,313,816 Mil.
Gross Profit was 2023685 + 1503655 + 468566 + 701560 = ₩4,697,466 Mil.
Total Current Assets was ₩2,702,773 Mil.
Total Assets was ₩21,921,051 Mil.
Property, Plant and Equipment(Net PPE) was ₩170,387 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩103,629 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,046,495 Mil.
Total Current Liabilities was ₩1,396,345 Mil.
Long-Term Debt & Capital Lease Obligation was ₩32,733 Mil.
Net Income was 1491924 + 1136505 + 740641 + 344901 = ₩3,713,971 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 85765 + 98159 + 13316 + -7286 = ₩189,954 Mil.
|
Total Receivables was ₩600,830 Mil.
Revenue was 2354213 + 40454 + 536163 + 11178 = ₩2,942,008 Mil.
Gross Profit was 24233 + -158797 + 536163 + -198410 = ₩203,189 Mil.
Total Current Assets was ₩2,288,523 Mil.
Total Assets was ₩17,970,008 Mil.
Property, Plant and Equipment(Net PPE) was ₩242,922 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩143,491 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,284,415 Mil.
Total Current Liabilities was ₩1,380,605 Mil.
Long-Term Debt & Capital Lease Obligation was ₩65,699 Mil.
|
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) |
| = | (1019074 / 5313816) | / | (600830 / 2942008) |
| = | 0.191778 | / | 0.204224 |
| | = | 0.9391 |
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) |
| = | (203189 / 2942008) | / | (4697466 / 5313816) |
| = | 0.069065 | / | 0.88401 |
| | = | 0.0781 |
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 - (2702773 + 170387) / 21921051) | / | (1 - (2288523 + 242922) / 17970008) |
| = | 0.868931 | / | 0.859129 |
| | = | 1.0114 |
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 |
| = | 5313816 | / | 2942008 |
| | = | 1.8062 |
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)) |
| = | (143491 / (143491 + 242922)) | / | (103629 / (103629 + 170387)) |
| = | 0.371341 | / | 0.378186 |
| | = | 0.9819 |
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) |
| = | (1046495 / 5313816) | / | (1284415 / 2942008) |
| = | 0.196939 | / | 0.436578 |
| | = | 0.4511 |
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) |
| = | ((32733 + 1396345) / 21921051) | / | ((65699 + 1380605) / 17970008) |
| = | 0.065192 | / | 0.080484 |
| | = | 0.81 |
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 |
| = | (3713971 - 0 | - | 189954) | / | 21921051 |
| | = | 0.160759 |
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.
SK Square has a M-score of -1.39 signals that the company is likely to be a manipulator.
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