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.
EQT Beneish M-Score Chart
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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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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.34 |
-3.04 |
-3.49 |
-2.12 |
3.90 |
Competitive Comparison of EQT's Beneish M-Score
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's Beneish M-Score Distribution in the Oil & Gas Industry
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 * 2.2185 | + | 0.528 * 14.1584 | + | 0.404 * 0.5627 | + | 0.892 * 0.3787 | + | 0.115 * 1.1451 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 2.7733 | + | 4.679 * -0.118444 | - | 0.327 * 0.8398 |
| = | 4.07 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was €493 Mil.
Revenue was 1201.296 + 1257.392 + 944.68 + 788.579 = €4,192 Mil.
Gross Profit was 157.786 + 202.07 + -56.755 + -110.316 = €193 Mil.
Total Current Assets was €1,928 Mil.
Total Assets was €23,403 Mil.
Property, Plant and Equipment(Net PPE) was €21,181 Mil.
Depreciation, Depletion and Amortization(DDA) was €1,707 Mil.
Selling, General, & Admin. Expense(SGA) was €238 Mil.
Total Current Liabilities was €2,184 Mil.
Long-Term Debt & Capital Lease Obligation was €4,506 Mil.
Net Income was 95.209 + 460.384 + 76.136 + -61.496 = €570 Mil.
Non Operating Income was 88.477 + 487.188 + 157.859 + 143.506 = €877 Mil.
Cash Flow from Operations was 1063.21 + 572.562 + 425.944 + 403.455 = €2,465 Mil.
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Total Receivables was €587 Mil.
Revenue was 1715.029 + 2428.659 + 3733.727 + 3190.482 = €11,068 Mil.
Gross Profit was 827.16 + 1501.902 + 2681.739 + 2195.855 = €7,207 Mil.
Total Current Assets was €3,689 Mil.
Total Assets was €21,193 Mil.
Property, Plant and Equipment(Net PPE) was €17,030 Mil.
Depreciation, Depletion and Amortization(DDA) was €1,590 Mil.
Selling, General, & Admin. Expense(SGA) was €226 Mil.
Total Current Liabilities was €2,489 Mil.
Long-Term Debt & Capital Lease Obligation was €4,725 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) |
| = | (492.955 / 4191.947) | / | (586.675 / 11067.897) |
| = | 0.117596 | / | 0.053007 |
| | = | 2.2185 |
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) |
| = | (7206.656 / 11067.897) | / | (192.785 / 4191.947) |
| = | 0.651131 | / | 0.045989 |
| | = | 14.1584 |
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 - (1928.117 + 21180.775) / 23403.254) | / | (1 - (3688.883 + 17030.276) / 21192.884) |
| = | 0.012578 | / | 0.022353 |
| | = | 0.5627 |
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 |
| = | 4191.947 | / | 11067.897 |
| | = | 0.3787 |
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)) |
| = | (1589.936 / (1589.936 + 17030.276)) | / | (1706.639 / (1706.639 + 21180.775)) |
| = | 0.085388 | / | 0.074567 |
| | = | 1.1451 |
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) |
| = | (237.691 / 4191.947) | / | (226.295 / 11067.897) |
| = | 0.056702 | / | 0.020446 |
| | = | 2.7733 |
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) |
| = | ((4505.952 + 2183.742) / 23403.254) | / | ((4724.698 + 2488.57) / 21192.884) |
| = | 0.285845 | / | 0.340363 |
| | = | 0.8398 |
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 |
| = | (570.233 - 877.03 | - | 2465.171) | / | 23403.254 |
| | = | -0.118444 |
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 4.07 signals that the company is likely to be a manipulator.
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