Koses Co Beneish M-Score Historical Data
The historical data trend for Koses 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.
Koses Co Beneish M-Score Chart
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Koses Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.27 |
-1.15 |
-2.41 |
-2.71 |
-0.27 |
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Koses Co Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.50 |
-2.58 |
-0.65 |
-0.27 |
-1.08 |
Competitive Comparison of Koses Co's Beneish M-Score
For the Semiconductor Equipment & Materials subindustry, Koses 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.
Koses Co's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Koses Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Koses Co's Beneish M-Score falls into.
Koses 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 Koses 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 | + | 0.528 * 1.4138 | + | 0.404 * 3.3055 | + | 0.892 * 1.5958 | + | 0.115 * 0.0368 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3178 | + | 4.679 * 0.230577 | - | 0.327 * 1.8473 |
| = | -1.08 |
* 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 ₩0 Mil.
Revenue was 16951.595 + 39840.401 + 23847.358 + 25067.91 = ₩105,707 Mil.
Gross Profit was 1613.613 + 1858.299 + 7291.1 + 6330.608 = ₩17,094 Mil.
Total Current Assets was ₩62,352 Mil.
Total Assets was ₩101,178 Mil.
Property, Plant and Equipment(Net PPE) was ₩0 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,066 Mil.
Selling, General, & Admin. Expense(SGA) was ₩4,609 Mil.
Total Current Liabilities was ₩30,449 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 Mil.
Net Income was 1825.034 + -3463.892 + 5715.037 + 4327.305 = ₩8,403 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 0 + -5506.658 + -9223.443 + -195.721 = ₩-14,926 Mil.
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Total Receivables was ₩9,685 Mil.
Revenue was 6894.87 + 20630.811 + 19097.684 + 19616.379 = ₩66,240 Mil.
Gross Profit was 1686.981 + 3554.398 + 4036.744 + 5865.569 = ₩15,144 Mil.
Total Current Assets was ₩34,963 Mil.
Total Assets was ₩74,077 Mil.
Property, Plant and Equipment(Net PPE) was ₩30,514 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,166 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,192 Mil.
Total Current Liabilities was ₩12,068 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 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) |
| = | (0 / 105707.264) | / | (9685.105 / 66239.744) |
| = | 0 | / | 0.146213 |
| | = | 0 |
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) |
| = | (15143.692 / 66239.744) | / | (17093.62 / 105707.264) |
| = | 0.228619 | / | 0.161707 |
| | = | 1.4138 |
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 - (62352.184 + 0) / 101177.867) | / | (1 - (34963.253 + 30514.177) / 74077.173) |
| = | 0.383737 | / | 0.116092 |
| | = | 3.3055 |
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 |
| = | 105707.264 | / | 66239.744 |
| | = | 1.5958 |
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)) |
| = | (1165.974 / (1165.974 + 30514.177)) | / | (1066.181 / (1066.181 + 0)) |
| = | 0.036805 | / | 1 |
| | = | 0.0368 |
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) |
| = | (4609.227 / 105707.264) | / | (2191.732 / 66239.744) |
| = | 0.043604 | / | 0.033088 |
| | = | 1.3178 |
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) |
| = | ((0 + 30449.223) / 101177.867) | / | ((0 + 12068.08) / 74077.173) |
| = | 0.300947 | / | 0.162912 |
| | = | 1.8473 |
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 |
| = | (8403.484 - 0 | - | -14925.822) | / | 101177.867 |
| | = | 0.230577 |
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.
Koses Co has a M-score of -1.08 signals that the company is likely to be a manipulator.
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