Yulho Co Beneish M-Score Historical Data
The historical data trend for Yulho 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.
Yulho Co Beneish M-Score Chart
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Yulho 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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-1.11 |
-3.33 |
-2.09 |
-1.67 |
-2.70 |
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Yulho Co Quarterly Data
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Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
| Beneish M-Score |
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-2.80 |
-1.95 |
-2.70 |
-2.17 |
-2.69 |
Competitive Comparison of Yulho Co's Beneish M-Score
For the Software - Application subindustry, Yulho 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.
Yulho Co's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Yulho Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Yulho Co's Beneish M-Score falls into.
Yulho 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 Yulho 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 * 1.5722 | + | 0.528 * 0.9665 | + | 0.404 * 0.7173 | + | 0.892 * 0.9513 | + | 0.115 * 1.2783 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9684 | + | 4.679 * -0.131744 | - | 0.327 * 0.9336 |
| = | -2.69 |
* 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 (Jun24) TTM: | Last Year (Jun23) TTM: |
Total Receivables was ₩25,901 Mil.
Revenue was 19370.572 + 9237.905 + 35648.918 + 25870.688 = ₩90,128 Mil.
Gross Profit was 6043.263 + 4149.899 + 7801.705 + 3814.567 = ₩21,809 Mil.
Total Current Assets was ₩79,626 Mil.
Total Assets was ₩129,510 Mil.
Property, Plant and Equipment(Net PPE) was ₩17,417 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩444 Mil.
Selling, General, & Admin. Expense(SGA) was ₩11,110 Mil.
Total Current Liabilities was ₩39,223 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,344 Mil.
Net Income was 153.318 + -2772.271 + -10120.757 + -1129.899 = ₩-13,870 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 1821.49 + -6585.77 + 7166.16 + 790.688 = ₩3,193 Mil.
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Total Receivables was ₩17,317 Mil.
Revenue was 15180.246 + 13299.422 + 34376.728 + 31884.645 = ₩94,741 Mil.
Gross Profit was 4909.897 + 4867.539 + 8056.054 + 4323.723 = ₩22,157 Mil.
Total Current Assets was ₩65,606 Mil.
Total Assets was ₩131,984 Mil.
Property, Plant and Equipment(Net PPE) was ₩20,248 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩665 Mil.
Selling, General, & Admin. Expense(SGA) was ₩12,060 Mil.
Total Current Liabilities was ₩44,239 Mil.
Long-Term Debt & Capital Lease Obligation was ₩3,319 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) |
| = | (25900.977 / 90128.083) | / | (17317.36 / 94741.041) |
| = | 0.28738 | / | 0.182786 |
| | = | 1.5722 |
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) |
| = | (22157.213 / 94741.041) | / | (21809.434 / 90128.083) |
| = | 0.233871 | / | 0.241983 |
| | = | 0.9665 |
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 - (79625.961 + 17417.32) / 129510.43) | / | (1 - (65606.259 + 20247.899) / 131984.376) |
| = | 0.250691 | / | 0.349513 |
| | = | 0.7173 |
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 |
| = | 90128.083 | / | 94741.041 |
| | = | 0.9513 |
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)) |
| = | (665.158 / (665.158 + 20247.899)) | / | (444.441 / (444.441 + 17417.32)) |
| = | 0.031806 | / | 0.024882 |
| | = | 1.2783 |
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) |
| = | (11110.151 / 90128.083) | / | (12060.105 / 94741.041) |
| = | 0.123271 | / | 0.127295 |
| | = | 0.9684 |
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) |
| = | ((4343.515 + 39223.432) / 129510.43) | / | ((3319.2 + 44239.351) / 131984.376) |
| = | 0.336397 | / | 0.360335 |
| | = | 0.9336 |
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 |
| = | (-13869.609 - 0 | - | 3192.568) | / | 129510.43 |
| | = | -0.131744 |
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.
Yulho Co has a M-score of -2.69 suggests that the company is unlikely to be a manipulator.
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