Hae In Beneish M-Score Historical Data
The historical data trend for Hae In'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.
Hae In Beneish M-Score Chart
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Hae In Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.95 |
-2.41 |
-3.01 |
-3.02 |
-1.75 |
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Hae In Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-3.02 |
-2.69 |
-2.61 |
-1.89 |
-1.75 |
Competitive Comparison of Hae In's Beneish M-Score
For the Industrial Distribution subindustry, Hae In'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.
Hae In's Beneish M-Score Distribution in the Industrial Distribution Industry
For the Industrial Distribution industry and Industrials sector, Hae In's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Hae In's Beneish M-Score falls into.
Hae In 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 Hae In 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 * 0.897 | + | 0.528 * 1.1633 | + | 0.404 * 1.0741 | + | 0.892 * 1.5508 | + | 0.115 * 1.167 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8365 | + | 4.679 * 0.036295 | - | 0.327 * 0.9962 |
| = | -1.75 |
* 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 ₩34,379 Mil.
Revenue was 88073.401 + 65892.484 + 71005.116 + 51109.699 = ₩276,081 Mil.
Gross Profit was 9851.199 + 9890.236 + 11747.423 + 6385.767 = ₩37,875 Mil.
Total Current Assets was ₩176,765 Mil.
Total Assets was ₩253,961 Mil.
Property, Plant and Equipment(Net PPE) was ₩64,032 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,567 Mil.
Selling, General, & Admin. Expense(SGA) was ₩10,955 Mil.
Total Current Liabilities was ₩133,607 Mil.
Long-Term Debt & Capital Lease Obligation was ₩2,959 Mil.
Net Income was 3451.356 + 1228.953 + 4019.445 + -1295.348 = ₩7,404 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 44299.475 + -37969.241 + -5831.252 + -2312.053 = ₩-1,813 Mil.
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Total Receivables was ₩24,714 Mil.
Revenue was 48831.055 + 45804.878 + 44545.449 + 38848.139 = ₩178,030 Mil.
Gross Profit was 6291.695 + 8100.606 + 7264.868 + 6754.642 = ₩28,412 Mil.
Total Current Assets was ₩164,239 Mil.
Total Assets was ₩240,522 Mil.
Property, Plant and Equipment(Net PPE) was ₩64,677 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩4,244 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,445 Mil.
Total Current Liabilities was ₩121,450 Mil.
Long-Term Debt & Capital Lease Obligation was ₩8,385 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) |
| = | (34378.844 / 276080.7) | / | (24713.75 / 178029.521) |
| = | 0.124525 | / | 0.138818 |
| | = | 0.897 |
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) |
| = | (28411.811 / 178029.521) | / | (37874.625 / 276080.7) |
| = | 0.15959 | / | 0.137187 |
| | = | 1.1633 |
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 - (176765.037 + 64032.408) / 253960.587) | / | (1 - (164239.14 + 64676.964) / 240522.146) |
| = | 0.051831 | / | 0.048254 |
| | = | 1.0741 |
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 |
| = | 276080.7 | / | 178029.521 |
| | = | 1.5508 |
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)) |
| = | (4243.961 / (4243.961 + 64676.964)) | / | (3566.97 / (3566.97 + 64032.408)) |
| = | 0.061577 | / | 0.052766 |
| | = | 1.167 |
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) |
| = | (10954.826 / 276080.7) | / | (8444.728 / 178029.521) |
| = | 0.03968 | / | 0.047434 |
| | = | 0.8365 |
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) |
| = | ((2958.886 + 133606.578) / 253960.587) | / | ((8384.555 + 121449.715) / 240522.146) |
| = | 0.537743 | / | 0.539802 |
| | = | 0.9962 |
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 |
| = | (7404.406 - 0 | - | -1813.071) | / | 253960.587 |
| | = | 0.036295 |
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.
Hae In has a M-score of -1.75 signals that the company is likely to be a manipulator.
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