EQT Beneish M-Score Historical Data
The historical data trend for EQT'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.
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EQT Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.21 |
-4.25 |
-1.66 |
-1.70 |
-2.12 |
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EQT 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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-1.70 |
-2.34 |
-3.04 |
-3.49 |
-2.12 |
Competitive Comparison
For the Oil & Gas E&P subindustry, EQT'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.
EQT Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, EQT's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where EQT's Beneish M-Score falls into.
EQT 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 EQT 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 * 1.3627 | + | 0.528 * 3.6339 | + | 0.404 * 0.5913 | + | 0.892 * 0.4176 | + | 0.115 * 1.2074 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 2.2384 | + | 4.679 * -0.122925 | - | 0.327 * 0.752 |
| = | -2.12 |
* 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 $915 Mil.
Revenue was 1371.202 + 1008.196 + 854.365 + 1836.219 = $5,070 Mil.
Gross Profit was 220.36 + -60.571 + -119.519 + 885.61 = $926 Mil.
Total Current Assets was $2,013 Mil.
Total Assets was $25,285 Mil.
Property, Plant and Equipment(Net PPE) was $22,950 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,749 Mil.
Selling, General, & Admin. Expense(SGA) was $236 Mil.
Total Current Liabilities was $2,037 Mil.
Long-Term Debt & Capital Lease Obligation was $5,503 Mil.
Net Income was 502.055 + 81.255 + -66.626 + 1218.548 = $1,735 Mil.
Non Operating Income was 531.285 + 168.473 + 155.478 + 809.323 = $1,665 Mil.
Cash Flow from Operations was 624.386 + 454.583 + 437.113 + 1662.768 = $3,179 Mil.
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Total Receivables was $1,608 Mil.
Revenue was 2572.732 + 3696.759 + 3372.603 + 2498.527 = $12,141 Mil.
Gross Profit was 1590.998 + 2655.187 + 2321.2 + 1489.313 = $8,057 Mil.
Total Current Assets was $4,014 Mil.
Total Assets was $22,670 Mil.
Property, Plant and Equipment(Net PPE) was $18,167 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,699 Mil.
Selling, General, & Admin. Expense(SGA) was $253 Mil.
Total Current Liabilities was $3,732 Mil.
Long-Term Debt & Capital Lease Obligation was $5,256 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) |
| = | (915.109 / 5069.982) | / | (1608.089 / 12140.621) |
| = | 0.180496 | / | 0.132455 |
| | = | 1.3627 |
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) |
| = | (8056.698 / 12140.621) | / | (925.88 / 5069.982) |
| = | 0.663615 | / | 0.18262 |
| | = | 3.6339 |
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 - (2012.975 + 22950.17) / 25285.098) | / | (1 - (4014.441 + 18167.333) / 22669.926) |
| = | 0.012733 | / | 0.021533 |
| | = | 0.5913 |
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 |
| = | 5069.982 | / | 12140.621 |
| | = | 0.4176 |
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)) |
| = | (1698.607 / (1698.607 + 18167.333)) | / | (1749.085 / (1749.085 + 22950.17)) |
| = | 0.085503 | / | 0.070815 |
| | = | 1.2074 |
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) |
| = | (236.171 / 5069.982) | / | (252.645 / 12140.621) |
| = | 0.046582 | / | 0.02081 |
| | = | 2.2384 |
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) |
| = | ((5502.681 + 2036.84) / 25285.098) | / | ((5256.333 + 3732.22) / 22669.926) |
| = | 0.29818 | / | 0.396497 |
| | = | 0.752 |
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 |
| = | (1735.232 - 1664.559 | - | 3178.85) | / | 25285.098 |
| | = | -0.122925 |
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.
EQT has a M-score of -2.12 suggests that the company is unlikely to be a manipulator.
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