Dongsuh Beneish M-Score Historical Data
The historical data trend for Dongsuh'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.
Dongsuh Beneish M-Score Chart
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Dongsuh Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.44 |
-2.28 |
-2.35 |
-2.16 |
-2.52 |
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Dongsuh 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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-2.16 |
-2.26 |
-2.28 |
-2.07 |
-2.52 |
Competitive Comparison of Dongsuh's Beneish M-Score
For the Food Distribution subindustry, Dongsuh'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.
Dongsuh's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, Dongsuh's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Dongsuh's Beneish M-Score falls into.
Dongsuh 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 Dongsuh 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 * 1.0498 | + | 0.528 * 0.833 | + | 0.404 * 0.9933 | + | 0.892 * 0.88 | + | 0.115 * 1.0753 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1399 | + | 4.679 * 0.015802 | - | 0.327 * 0.8389 |
| = | -2.52 |
* 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 ₩61,834 Mil.
Revenue was 114944.889 + 121187.084 + 129722.881 + 123840.687 = ₩489,696 Mil.
Gross Profit was 19984.824 + 20672.606 + 22373.921 + 23312.636 = ₩86,344 Mil.
Total Current Assets was ₩851,965 Mil.
Total Assets was ₩1,694,020 Mil.
Property, Plant and Equipment(Net PPE) was ₩47,758 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩4,736 Mil.
Selling, General, & Admin. Expense(SGA) was ₩23,817 Mil.
Total Current Liabilities was ₩57,996 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,266 Mil.
Net Income was 30999.292 + 36196.49 + 38119.881 + 39543.627 = ₩144,859 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 19122.802 + 21385.27 + 9155.165 + 68427.667 = ₩118,091 Mil.
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Total Receivables was ₩66,937 Mil.
Revenue was 127741.885 + 140451.428 + 150121.457 + 138171.838 = ₩556,487 Mil.
Gross Profit was 20008.092 + 18633.42 + 21544.079 + 21551.038 = ₩81,737 Mil.
Total Current Assets was ₩812,499 Mil.
Total Assets was ₩1,627,853 Mil.
Property, Plant and Equipment(Net PPE) was ₩46,954 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,044 Mil.
Selling, General, & Admin. Expense(SGA) was ₩23,744 Mil.
Total Current Liabilities was ₩67,708 Mil.
Long-Term Debt & Capital Lease Obligation was ₩176 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) |
| = | (61833.662 / 489695.541) | / | (66937.208 / 556486.608) |
| = | 0.12627 | / | 0.120285 |
| | = | 1.0498 |
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) |
| = | (81736.629 / 556486.608) | / | (86343.987 / 489695.541) |
| = | 0.14688 | / | 0.176322 |
| | = | 0.833 |
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 - (851964.86 + 47758.206) / 1694019.808) | / | (1 - (812498.509 + 46954.231) / 1627852.719) |
| = | 0.468883 | / | 0.472033 |
| | = | 0.9933 |
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 |
| = | 489695.541 | / | 556486.608 |
| | = | 0.88 |
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)) |
| = | (5044.31 / (5044.31 + 46954.231)) | / | (4735.97 / (4735.97 + 47758.206)) |
| = | 0.097009 | / | 0.090219 |
| | = | 1.0753 |
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) |
| = | (23817.129 / 489695.541) | / | (23743.706 / 556486.608) |
| = | 0.048637 | / | 0.042667 |
| | = | 1.1399 |
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) |
| = | ((1266.047 + 57996.437) / 1694019.808) | / | ((175.594 + 67707.638) / 1627852.719) |
| = | 0.034983 | / | 0.041701 |
| | = | 0.8389 |
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 |
| = | (144859.29 - 0 | - | 118090.904) | / | 1694019.808 |
| | = | 0.015802 |
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.
Dongsuh has a M-score of -2.52 suggests that the company is unlikely to be a manipulator.
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