GSE Co Beneish M-Score Historical Data
The historical data trend for GSE Co'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.
GSE Co Beneish M-Score Chart
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GSE Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.74 |
-2.89 |
-2.78 |
-1.98 |
-2.63 |
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GSE Co 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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-1.98 |
-2.52 |
-2.60 |
-1.88 |
-2.63 |
Competitive Comparison of GSE Co's Beneish M-Score
For the Utilities - Regulated Gas subindustry, GSE Co'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.
GSE Co's Beneish M-Score Distribution in the Utilities - Regulated Industry
For the Utilities - Regulated industry and Utilities sector, GSE Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where GSE Co's Beneish M-Score falls into.
GSE Co 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 GSE Co 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 * 0.9946 | + | 0.528 * 0.9626 | + | 0.404 * 0.9922 | + | 0.892 * 0.9776 | + | 0.115 * 0.9817 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0979 | + | 4.679 * -0.022339 | - | 0.327 * 0.9407 |
| = | -2.63 |
* 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 ₩50,955 Mil.
Revenue was 52886.089 + 24977.193 + 26628.649 + 64267.744 = ₩168,760 Mil.
Gross Profit was 7324.254 + 5394.613 + 6276.721 + 9503.266 = ₩28,499 Mil.
Total Current Assets was ₩64,759 Mil.
Total Assets was ₩209,399 Mil.
Property, Plant and Equipment(Net PPE) was ₩142,532 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩7,464 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,132 Mil.
Total Current Liabilities was ₩52,077 Mil.
Long-Term Debt & Capital Lease Obligation was ₩16,507 Mil.
Net Income was 933.415 + -466.698 + 1975.43 + 3146.281 = ₩5,588 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3438.143 + 383.327 + 175.221 + 6269.406 = ₩10,266 Mil.
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Total Receivables was ₩52,402 Mil.
Revenue was 55359.736 + 25709.51 + 33736.338 + 57812.734 = ₩172,618 Mil.
Gross Profit was 6255.934 + 5251.538 + 6727.29 + 9824.16 = ₩28,059 Mil.
Total Current Assets was ₩63,468 Mil.
Total Assets was ₩204,667 Mil.
Property, Plant and Equipment(Net PPE) was ₩139,123 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩7,145 Mil.
Selling, General, & Admin. Expense(SGA) was ₩7,576 Mil.
Total Current Liabilities was ₩55,820 Mil.
Long-Term Debt & Capital Lease Obligation was ₩15,443 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) |
| = | (50954.989 / 168759.675) | / | (52401.622 / 172618.318) |
| = | 0.301938 | / | 0.303569 |
| | = | 0.9946 |
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) |
| = | (28058.922 / 172618.318) | / | (28498.854 / 168759.675) |
| = | 0.162549 | / | 0.168872 |
| | = | 0.9626 |
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 - (64758.779 + 142532.386) / 209399.15) | / | (1 - (63467.795 + 139123.072) / 204667.325) |
| = | 0.010067 | / | 0.010146 |
| | = | 0.9922 |
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 |
| = | 168759.675 | / | 172618.318 |
| | = | 0.9776 |
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)) |
| = | (7144.945 / (7144.945 + 139123.072)) | / | (7463.992 / (7463.992 + 142532.386)) |
| = | 0.048848 | / | 0.049761 |
| | = | 0.9817 |
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) |
| = | (8132.463 / 168759.675) | / | (7576.377 / 172618.318) |
| = | 0.04819 | / | 0.043891 |
| | = | 1.0979 |
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) |
| = | ((16506.706 + 52076.993) / 209399.15) | / | ((15442.774 + 55820.168) / 204667.325) |
| = | 0.327526 | / | 0.348189 |
| | = | 0.9407 |
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 |
| = | (5588.428 - 0 | - | 10266.097) | / | 209399.15 |
| | = | -0.022339 |
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.
GSE Co has a M-score of -2.63 suggests that the company is unlikely to be a manipulator.
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