Cu Tech Beneish M-Score Historical Data
The historical data trend for Cu Tech'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.
Cu Tech Beneish M-Score Chart
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Cu Tech Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-1.27 |
-2.16 |
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Cu Tech Quarterly Data
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Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.91 |
-2.16 |
-1.19 |
-2.38 |
-2.59 |
Competitive Comparison of Cu Tech's Beneish M-Score
For the Electronic Components subindustry, Cu Tech'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.
Cu Tech's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Cu Tech's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cu Tech's Beneish M-Score falls into.
Cu Tech 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 Cu Tech 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 * 0.8531 | + | 0.528 * 0.7436 | + | 0.404 * 0.6592 | + | 0.892 * 1.5818 | + | 0.115 * 1.0026 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9993 | + | 4.679 * -0.033819 | - | 0.327 * 1.2014 |
| = | -2.59 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was ₩28,021 Mil.
Revenue was 70024.989 + 61496.642 + 73016.286 + 69111.212 = ₩273,649 Mil.
Gross Profit was 4772.178 + 4723.186 + 6001.041 + 5636.334 = ₩21,133 Mil.
Total Current Assets was ₩121,458 Mil.
Total Assets was ₩152,853 Mil.
Property, Plant and Equipment(Net PPE) was ₩26,201 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,986 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,668 Mil.
Total Current Liabilities was ₩36,149 Mil.
Long-Term Debt & Capital Lease Obligation was ₩6,493 Mil.
Net Income was -415.834 + 3132.233 + 4583.046 + 223.606 = ₩7,523 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 782.048 + 7139.231 + 5169.388 + -398.331 = ₩12,692 Mil.
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Total Receivables was ₩20,766 Mil.
Revenue was 42361.163 + 28272.568 + 33184.012 + 69180.142 = ₩172,998 Mil.
Gross Profit was 3039.109 + 212.536 + 1962.43 + 4719.981 = ₩9,934 Mil.
Total Current Assets was ₩100,697 Mil.
Total Assets was ₩134,083 Mil.
Property, Plant and Equipment(Net PPE) was ₩26,475 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩4,039 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,321 Mil.
Total Current Liabilities was ₩24,096 Mil.
Long-Term Debt & Capital Lease Obligation was ₩7,038 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) |
| = | (28020.891 / 273649.129) | / | (20765.921 / 172997.885) |
| = | 0.102397 | / | 0.120036 |
| | = | 0.8531 |
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) |
| = | (9934.056 / 172997.885) | / | (21132.739 / 273649.129) |
| = | 0.057423 | / | 0.077226 |
| | = | 0.7436 |
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 - (121458.314 + 26200.988) / 152853.012) | / | (1 - (100697.334 + 26474.525) / 134083.031) |
| = | 0.033978 | / | 0.051544 |
| | = | 0.6592 |
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 |
| = | 273649.129 | / | 172997.885 |
| | = | 1.5818 |
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)) |
| = | (4039.337 / (4039.337 + 26474.525)) | / | (3985.614 / (3985.614 + 26200.988)) |
| = | 0.132377 | / | 0.132033 |
| | = | 1.0026 |
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) |
| = | (3668.499 / 273649.129) | / | (2320.97 / 172997.885) |
| = | 0.013406 | / | 0.013416 |
| | = | 0.9993 |
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) |
| = | ((6492.56 + 36149.39) / 152853.012) | / | ((7038.338 + 24096.499) / 134083.031) |
| = | 0.278974 | / | 0.232206 |
| | = | 1.2014 |
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 |
| = | (7523.051 - 0 | - | 12692.336) | / | 152853.012 |
| | = | -0.033819 |
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.
Cu Tech has a M-score of -2.59 suggests that the company is unlikely to be a manipulator.
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