Ggumbi Beneish M-Score Historical Data
The historical data trend for Ggumbi'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.
Ggumbi Beneish M-Score Chart
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Ggumbi Annual Data
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Trend |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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- |
- |
- |
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Ggumbi Quarterly Data
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Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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- |
- |
- |
-1.36 |
-0.18 |
Competitive Comparison of Ggumbi's Beneish M-Score
For the Furnishings, Fixtures & Appliances subindustry, Ggumbi'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.
Ggumbi's Beneish M-Score Distribution in the Furnishings, Fixtures & Appliances Industry
For the Furnishings, Fixtures & Appliances industry and Consumer Cyclical sector, Ggumbi's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ggumbi's Beneish M-Score falls into.
Ggumbi 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 Ggumbi 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 | + | 0.528 * 1.0772 | + | 0.404 * 7.8357 | + | 0.892 * 1.1445 | + | 0.115 * 0.0852 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3433 | + | 4.679 * 0.056518 | - | 0.327 * 0.4319 |
| = | -0.18 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩0 Mil.
Revenue was 9089.408 + 8032.545 + 7807.005 + 6226.713 = ₩31,156 Mil.
Gross Profit was 2734.439 + 2177.319 + 2184.214 + 1653.479 = ₩8,749 Mil.
Total Current Assets was ₩28,899 Mil.
Total Assets was ₩49,392 Mil.
Property, Plant and Equipment(Net PPE) was ₩0 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩395 Mil.
Selling, General, & Admin. Expense(SGA) was ₩5,864 Mil.
Total Current Liabilities was ₩7,218 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 Mil.
Net Income was -187.568 + -230.422 + -175.82 + -738.345 = ₩-1,332 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 0 + -1522.943 + -1342.617 + -1258.145 = ₩-4,124 Mil.
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Total Receivables was ₩4,540 Mil.
Revenue was 6861.659 + 6496.647 + 6764.6 + 7099.717 = ₩27,223 Mil.
Gross Profit was 1877.874 + 1743.024 + 2206.714 + 2407.179 = ₩8,235 Mil.
Total Current Assets was ₩15,867 Mil.
Total Assets was ₩24,023 Mil.
Property, Plant and Equipment(Net PPE) was ₩6,884 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩641 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,814 Mil.
Total Current Liabilities was ₩6,195 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,933 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) |
| = | (0 / 31155.671) | / | (4539.836 / 27222.623) |
| = | 0 | / | 0.166767 |
| | = | 0 |
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) |
| = | (8234.791 / 27222.623) | / | (8749.451 / 31155.671) |
| = | 0.302498 | / | 0.28083 |
| | = | 1.0772 |
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 - (28898.615 + 0) / 49392.333) | / | (1 - (15867.385 + 6883.693) / 24023.161) |
| = | 0.414917 | / | 0.052952 |
| | = | 7.8357 |
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 |
| = | 31155.671 | / | 27222.623 |
| | = | 1.1445 |
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)) |
| = | (641.119 / (641.119 + 6883.693)) | / | (394.67 / (394.67 + 0)) |
| = | 0.085201 | / | 1 |
| | = | 0.0852 |
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) |
| = | (5863.713 / 31155.671) | / | (3814.129 / 27222.623) |
| = | 0.188207 | / | 0.140109 |
| | = | 1.3433 |
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) |
| = | ((0 + 7217.564) / 49392.333) | / | ((1933.26 + 6195.399) / 24023.161) |
| = | 0.146127 | / | 0.338368 |
| | = | 0.4319 |
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 |
| = | (-1332.155 - 0 | - | -4123.705) | / | 49392.333 |
| | = | 0.056518 |
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.
Ggumbi has a M-score of -0.18 signals that the company is likely to be a manipulator.
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