GeoPark Beneish M-Score Historical Data
The historical data trend for GeoPark'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.
GeoPark Beneish M-Score Chart
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GeoPark Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.94 |
-3.66 |
-2.33 |
-2.99 |
-3.07 |
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GeoPark 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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-2.99 |
-3.77 |
-3.35 |
-2.57 |
-3.07 |
Competitive Comparison of GeoPark's Beneish M-Score
For the Oil & Gas E&P subindustry, GeoPark'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.
GeoPark's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, GeoPark's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where GeoPark's Beneish M-Score falls into.
GeoPark 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 GeoPark 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 * 1.3435 | + | 0.528 * 1.06 | + | 0.404 * 0.9463 | + | 0.892 * 0.7209 | + | 0.115 * 0.8351 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.346 | + | 4.679 * -0.128036 | - | 0.327 * 0.966 |
| = | -3.07 |
* 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 $90.9 Mil.
Revenue was 199.063 + 192.785 + 182.326 + 182.451 = $756.6 Mil.
Gross Profit was 103.576 + 104.758 + 92.28 + 102.752 = $403.4 Mil.
Total Current Assets was $269.7 Mil.
Total Assets was $1,016.5 Mil.
Property, Plant and Equipment(Net PPE) was $715.3 Mil.
Depreciation, Depletion and Amortization(DDA) was $120.9 Mil.
Selling, General, & Admin. Expense(SGA) was $54.3 Mil.
Total Current Liabilities was $230.5 Mil.
Long-Term Debt & Capital Lease Obligation was $511.8 Mil.
Net Income was 26.293 + 24.768 + 33.75 + 26.257 = $111.1 Mil.
Non Operating Income was -20.599 + -13.949 + -11.195 + -13.972 = $-59.7 Mil.
Cash Flow from Operations was 110.624 + 92.609 + 5.782 + 91.923 = $300.9 Mil.
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Total Receivables was $93.9 Mil.
Revenue was 230.95 + 258.249 + 311.229 + 249.151 = $1,049.6 Mil.
Gross Profit was 123.479 + 149.699 + 172.962 + 146.968 = $593.1 Mil.
Total Current Assets was $238.1 Mil.
Total Assets was $974.0 Mil.
Property, Plant and Equipment(Net PPE) was $703.9 Mil.
Depreciation, Depletion and Amortization(DDA) was $96.7 Mil.
Selling, General, & Admin. Expense(SGA) was $56.0 Mil.
Total Current Liabilities was $229.2 Mil.
Long-Term Debt & Capital Lease Obligation was $507.2 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) |
| = | (90.945 / 756.625) | / | (93.9 / 1049.579) |
| = | 0.120198 | / | 0.089464 |
| | = | 1.3435 |
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) |
| = | (593.108 / 1049.579) | / | (403.366 / 756.625) |
| = | 0.565091 | / | 0.533112 |
| | = | 1.06 |
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 - (269.727 + 715.275) / 1016.549) | / | (1 - (238.144 + 703.89) / 973.975) |
| = | 0.031033 | / | 0.032794 |
| | = | 0.9463 |
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 |
| = | 756.625 | / | 1049.579 |
| | = | 0.7209 |
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)) |
| = | (96.692 / (96.692 + 703.89)) | / | (120.934 / (120.934 + 715.275)) |
| = | 0.120777 | / | 0.144622 |
| | = | 0.8351 |
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) |
| = | (54.291 / 756.625) | / | (55.953 / 1049.579) |
| = | 0.071754 | / | 0.05331 |
| | = | 1.346 |
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) |
| = | ((511.84 + 230.543) / 1016.549) | / | ((507.165 + 229.155) / 973.975) |
| = | 0.730297 | / | 0.755995 |
| | = | 0.966 |
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 |
| = | (111.068 - -59.715 | - | 300.938) | / | 1016.549 |
| | = | -0.128036 |
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.
GeoPark has a M-score of -3.07 suggests that the company is unlikely to be a manipulator.
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