Ecopetrol Beneish M-Score Historical Data
The historical data trend for Ecopetrol'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.
Ecopetrol Beneish M-Score Chart
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Ecopetrol Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.00 |
-2.28 |
-1.01 |
-1.78 |
-2.21 |
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Ecopetrol 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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- |
-2.21 |
-1.96 |
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Competitive Comparison of Ecopetrol's Beneish M-Score
For the Oil & Gas Integrated subindustry, Ecopetrol'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.
Ecopetrol's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Ecopetrol's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ecopetrol's Beneish M-Score falls into.
Ecopetrol 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 Ecopetrol 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 * | + | 0.528 * | + | 0.404 * | + | 0.892 * | + | 0.115 * |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * | + | 4.679 * | - | 0.327 * |
| = | |
* 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 R$44,768 Mil.
Revenue was 45889.756 + 45596.954 + 39706.881 + 42700.718 = R$173,894 Mil.
Gross Profit was 15863.24 + 16835.705 + 15525.287 + 14188.558 = R$62,413 Mil.
Total Current Assets was R$86,782 Mil.
Total Assets was R$396,170 Mil.
Property, Plant and Equipment(Net PPE) was R$204,933 Mil.
Depreciation, Depletion and Amortization(DDA) was R$256 Mil.
Selling, General, & Admin. Expense(SGA) was R$2,457 Mil.
Total Current Liabilities was R$58,500 Mil.
Long-Term Debt & Capital Lease Obligation was R$138,325 Mil.
Net Income was 4838.666 + 3675.909 + 5089.26 + 7617.366 = R$21,221 Mil.
Non Operating Income was 153.819 + -77.093 + 249.896 + -92.893 = R$234 Mil.
Cash Flow from Operations was 0 + 0 + 0 + 0 = R$0 Mil.
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Total Receivables was R$0 Mil.
Revenue was 42787.095 + 37544.295 + 41866.549 + 43676.236 = R$165,874 Mil.
Gross Profit was 17690.935 + 14024.929 + 17321.377 + 17280.736 = R$66,318 Mil.
Total Current Assets was R$0 Mil.
Total Assets was R$0 Mil.
Property, Plant and Equipment(Net PPE) was R$0 Mil.
Depreciation, Depletion and Amortization(DDA) was R$10,944 Mil.
Selling, General, & Admin. Expense(SGA) was R$5,280 Mil.
Total Current Liabilities was R$0 Mil.
Long-Term Debt & Capital Lease Obligation was R$0 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) |
| = | (44767.822 / 173894.309) | / | (0 / 165874.175) |
| = | 0.257443 | / | 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) |
| = | (66317.977 / 165874.175) | / | (62412.79 / 173894.309) |
| = | 0.399809 | / | 0.358912 |
| | = | |
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 - (86782.195 + 204933.468) / 396169.601) | / | (1 - (0 + 0) / 0) |
| = | 0.26366 | / | |
| | = | |
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 |
| = | 173894.309 | / | 165874.175 |
| | = | |
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)) |
| = | (10944.284 / (10944.284 + 0)) | / | (256.124 / (256.124 + 204933.468)) |
| = | 1 | / | 0.001248 |
| | = | |
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) |
| = | (2457.491 / 173894.309) | / | (5280.107 / 165874.175) |
| = | 0.014132 | / | 0.031832 |
| | = | |
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) |
| = | ((138324.935 + 58499.937) / 396169.601) | / | ((0 + 0) / 0) |
| = | 0.49682 | / | |
| | = | |
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 |
| = | (21221.201 - 233.729 | - | 0) | / | 396169.601 |
| | = | 0.052976 |
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.
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