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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Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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Ggumbi Quarterly Data
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Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.36 |
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 * 1.0025 | + | 0.528 * 1.2122 | + | 0.404 * 1.9068 | + | 0.892 * 1.0642 | + | 0.115 * 3.0225 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2016 | + | 4.679 * 0.050869 | - | 0.327 * 0.5551 |
| = | -1.36 |
* 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 ₩4,381 Mil.
Revenue was 8032.545 + 7807.005 + 6226.713 + 6861.659 = ₩28,928 Mil.
Gross Profit was 2177.319 + 2184.214 + 1653.479 + 1877.874 = ₩7,893 Mil.
Total Current Assets was ₩30,893 Mil.
Total Assets was ₩49,206 Mil.
Property, Plant and Equipment(Net PPE) was ₩14,027 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩495 Mil.
Selling, General, & Admin. Expense(SGA) was ₩4,302 Mil.
Total Current Liabilities was ₩8,106 Mil.
Long-Term Debt & Capital Lease Obligation was ₩5,416 Mil.
Net Income was -230.422 + -175.82 + -738.345 + -1155.343 = ₩-2,300 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -1522.943 + -1342.617 + -1258.145 + -679.316 = ₩-4,803 Mil.
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Total Receivables was ₩4,106 Mil.
Revenue was 6496.647 + 6764.6 + 7099.717 + 6820.78 = ₩27,182 Mil.
Gross Profit was 1743.024 + 2206.714 + 2407.179 + 2633.158 = ₩8,990 Mil.
Total Current Assets was ₩8,973 Mil.
Total Assets was ₩15,964 Mil.
Property, Plant and Equipment(Net PPE) was ₩6,261 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩718 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,364 Mil.
Total Current Liabilities was ₩5,920 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,983 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) |
| = | (4381.137 / 28927.922) | / | (4106.26 / 27181.744) |
| = | 0.15145 | / | 0.151067 |
| | = | 1.0025 |
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) |
| = | (8990.075 / 27181.744) | / | (7892.886 / 28927.922) |
| = | 0.330739 | / | 0.272847 |
| | = | 1.2122 |
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 - (30892.801 + 14027.105) / 49206.485) | / | (1 - (8973.155 + 6261.129) / 15963.573) |
| = | 0.087114 | / | 0.045685 |
| | = | 1.9068 |
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 |
| = | 28927.922 | / | 27181.744 |
| | = | 1.0642 |
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)) |
| = | (718.447 / (718.447 + 6261.129)) | / | (494.572 / (494.572 + 14027.105)) |
| = | 0.102936 | / | 0.034057 |
| | = | 3.0225 |
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) |
| = | (4301.752 / 28927.922) | / | (3363.833 / 27181.744) |
| = | 0.148706 | / | 0.123753 |
| | = | 1.2016 |
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) |
| = | ((5415.587 + 8106.378) / 49206.485) | / | ((1983.24 + 5919.845) / 15963.573) |
| = | 0.2748 | / | 0.49507 |
| | = | 0.5551 |
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 |
| = | (-2299.93 - 0 | - | -4803.021) | / | 49206.485 |
| | = | 0.050869 |
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 -1.36 signals that the company is likely to be a manipulator.
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