Konan Technology Beneish M-Score Historical Data
The historical data trend for Konan Technology'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.
Konan Technology Beneish M-Score Chart
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Konan Technology Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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- |
- |
- |
- |
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Konan Technology Quarterly Data
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Mar21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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|
|
|
- |
- |
- |
0.12 |
-1.64 |
Competitive Comparison of Konan Technology's Beneish M-Score
For the Software - Infrastructure subindustry, Konan Technology'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.
Konan Technology's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Konan Technology's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Konan Technology's Beneish M-Score falls into.
Konan Technology 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 Konan Technology 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 * 1.5942 | + | 0.528 * 1.6048 | + | 0.404 * 1.2427 | + | 0.892 * 1.5875 | + | 0.115 * 1.6813 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1671 | + | 4.679 * -0.062357 | - | 0.327 * 2.2491 |
| = | -1.64 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was ₩9,256 Mil.
Revenue was 16753.507 + 3110.937 + 2421.61 + 2142.202 = ₩24,428 Mil.
Gross Profit was 6656.555 + -889.268 + -136.036 + -604.825 = ₩5,026 Mil.
Total Current Assets was ₩33,017 Mil.
Total Assets was ₩48,094 Mil.
Property, Plant and Equipment(Net PPE) was ₩12,234 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,293 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,162 Mil.
Total Current Liabilities was ₩13,966 Mil.
Long-Term Debt & Capital Lease Obligation was ₩2,017 Mil.
Net Income was 2197.145 + -5188.424 + -3975.914 + -2869.167 = ₩-9,836 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -841.362 + -321.782 + -4772.333 + -901.891 = ₩-6,837 Mil.
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Total Receivables was ₩3,657 Mil.
Revenue was 7482.611 + 2624.074 + 2662.965 + 2618.519 = ₩15,388 Mil.
Gross Profit was 4469.747 + -273.909 + 233.756 + 651.648 = ₩5,081 Mil.
Total Current Assets was ₩45,459 Mil.
Total Assets was ₩49,868 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,037 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩736 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,707 Mil.
Total Current Liabilities was ₩6,879 Mil.
Long-Term Debt & Capital Lease Obligation was ₩489 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) |
| = | (9256.048 / 24428.256) | / | (3657.406 / 15388.169) |
| = | 0.378907 | / | 0.237676 |
| | = | 1.5942 |
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) |
| = | (5081.242 / 15388.169) | / | (5026.426 / 24428.256) |
| = | 0.330204 | / | 0.205763 |
| | = | 1.6048 |
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 - (33016.656 + 12233.668) / 48093.874) | / | (1 - (45458.82 + 2036.978) / 49868.456) |
| = | 0.059125 | / | 0.047578 |
| | = | 1.2427 |
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 |
| = | 24428.256 | / | 15388.169 |
| | = | 1.5875 |
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)) |
| = | (736.08 / (736.08 + 2036.978)) | / | (2293.487 / (2293.487 + 12233.668)) |
| = | 0.26544 | / | 0.157876 |
| | = | 1.6813 |
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) |
| = | (3162.256 / 24428.256) | / | (1706.85 / 15388.169) |
| = | 0.129451 | / | 0.11092 |
| | = | 1.1671 |
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) |
| = | ((2016.684 + 13965.526) / 48093.874) | / | ((489.318 + 6879.051) / 49868.456) |
| = | 0.332313 | / | 0.147756 |
| | = | 2.2491 |
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 |
| = | (-9836.36 - 0 | - | -6837.368) | / | 48093.874 |
| | = | -0.062357 |
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.
Konan Technology has a M-score of -1.64 signals that the company is likely to be a manipulator.
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