S-Oil Beneish M-Score Historical Data
The historical data trend for S-Oil'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.
S-Oil Beneish M-Score Chart
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S-Oil Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.80 |
-4.39 |
-2.25 |
-2.05 |
-2.51 |
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S-Oil Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.13 |
-2.51 |
-2.35 |
-2.37 |
-2.30 |
Competitive Comparison of S-Oil's Beneish M-Score
For the Oil & Gas Refining & Marketing subindustry, S-Oil'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.
S-Oil's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, S-Oil's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where S-Oil's Beneish M-Score falls into.
S-Oil 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 S-Oil 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 * 0.9184 | + | 0.528 * 2.1299 | + | 0.404 * 0.9824 | + | 0.892 * 1.029 | + | 0.115 * 1.0686 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.114 | + | 4.679 * -0.072229 | - | 0.327 * 1.043 |
| = | -2.30 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was ₩2,756,328 Mil.
Revenue was 8840623 + 9570838 + 9308489 + 9829913 = ₩37,549,863 Mil.
Gross Profit was -225743 + 358841 + 656434 + 165593 = ₩955,125 Mil.
Total Current Assets was ₩9,479,671 Mil.
Total Assets was ₩22,523,390 Mil.
Property, Plant and Equipment(Net PPE) was ₩12,276,656 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩752,850 Mil.
Selling, General, & Admin. Expense(SGA) was ₩546,116 Mil.
Total Current Liabilities was ₩10,332,957 Mil.
Long-Term Debt & Capital Lease Obligation was ₩2,990,668 Mil.
Net Income was -206188 + -21337 + 166203 + 160517 = ₩99,195 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 50451 + 79220 + -118960 + 1715329 = ₩1,726,040 Mil.
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Total Receivables was ₩2,916,679 Mil.
Revenue was 8999555 + 7819591 + 9077635 + 10593964 = ₩36,490,745 Mil.
Gross Profit was 1042686 + 207111 + 690355 + 36824 = ₩1,976,976 Mil.
Total Current Assets was ₩10,450,579 Mil.
Total Assets was ₩21,748,598 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,544,077 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩693,900 Mil.
Selling, General, & Admin. Expense(SGA) was ₩476,422 Mil.
Total Current Liabilities was ₩9,298,465 Mil.
Long-Term Debt & Capital Lease Obligation was ₩3,036,343 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) |
| = | (2756328 / 37549863) | / | (2916679 / 36490745) |
| = | 0.073404 | / | 0.079929 |
| | = | 0.9184 |
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) |
| = | (1976976 / 36490745) | / | (955125 / 37549863) |
| = | 0.054177 | / | 0.025436 |
| | = | 2.1299 |
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 - (9479671 + 12276656) / 22523390) | / | (1 - (10450579 + 10544077) / 21748598) |
| = | 0.034056 | / | 0.034666 |
| | = | 0.9824 |
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 |
| = | 37549863 | / | 36490745 |
| | = | 1.029 |
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)) |
| = | (693900 / (693900 + 10544077)) | / | (752850 / (752850 + 12276656)) |
| = | 0.061746 | / | 0.05778 |
| | = | 1.0686 |
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) |
| = | (546116 / 37549863) | / | (476422 / 36490745) |
| = | 0.014544 | / | 0.013056 |
| | = | 1.114 |
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) |
| = | ((2990668 + 10332957) / 22523390) | / | ((3036343 + 9298465) / 21748598) |
| = | 0.591546 | / | 0.567154 |
| | = | 1.043 |
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 |
| = | (99195 - 0 | - | 1726040) | / | 22523390 |
| | = | -0.072229 |
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.
S-Oil has a M-score of -2.30 suggests that the company is unlikely to be a manipulator.
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