W&T Offshore Beneish M-Score Historical Data
The historical data trend for W&T Offshore'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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W&T Offshore Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
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-3.28 |
-3.32 |
-2.22 |
-1.72 |
-3.38 |
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W&T Offshore 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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|
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|
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|
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-1.72 |
-2.41 |
-2.53 |
-2.32 |
-3.38 |
Competitive Comparison
For the Oil & Gas E&P subindustry, W&T Offshore'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.
W&T Offshore Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, W&T Offshore's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where W&T Offshore's Beneish M-Score falls into.
W&T Offshore 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 W&T Offshore 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 * 1.5054 | + | 0.528 * 1.1497 | + | 0.404 * 0.9916 | + | 0.892 * 0.5783 | + | 0.115 * 0.9554 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.9324 | + | 4.679 * -0.20408 | - | 0.327 * 0.8281 |
| = | -3.38 |
* 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 $69.8 Mil.
Revenue was 132.34 + 142.411 + 126.181 + 131.725 = $532.7 Mil.
Gross Profit was 92.062 + 105.501 + 91.202 + 102.965 = $391.7 Mil.
Total Current Assets was $265.0 Mil.
Total Assets was $1,114.0 Mil.
Property, Plant and Equipment(Net PPE) was $759.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $143.7 Mil.
Selling, General, & Admin. Expense(SGA) was $333.2 Mil.
Total Current Liabilities was $216.9 Mil.
Long-Term Debt & Capital Lease Obligation was $372.0 Mil.
Net Income was -0.443 + 2.145 + -12.109 + 26.005 = $15.6 Mil.
Non Operating Income was 92.547 + -3.418 + -0.518 + 39.007 = $127.6 Mil.
Cash Flow from Operations was 35.664 + 30.03 + 26.197 + 23.435 = $115.3 Mil.
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Total Receivables was $80.1 Mil.
Revenue was 189.7 + 266.485 + 273.808 + 191.004 = $921.0 Mil.
Gross Profit was 153.945 + 226.793 + 236.948 + 161.062 = $778.7 Mil.
Total Current Assets was $570.3 Mil.
Total Assets was $1,431.8 Mil.
Property, Plant and Equipment(Net PPE) was $745.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $133.6 Mil.
Selling, General, & Admin. Expense(SGA) was $298.2 Mil.
Total Current Liabilities was $792.3 Mil.
Long-Term Debt & Capital Lease Obligation was $121.7 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) |
| = | (69.778 / 532.657) | / | (80.146 / 920.997) |
| = | 0.131 | / | 0.087021 |
| | = | 1.5054 |
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) |
| = | (778.748 / 920.997) | / | (391.73 / 532.657) |
| = | 0.845549 | / | 0.735426 |
| | = | 1.1497 |
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 - (264.98 + 759.571) / 1114.005) | / | (1 - (570.263 + 745.579) / 1431.79) |
| = | 0.080299 | / | 0.080981 |
| | = | 0.9916 |
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 |
| = | 532.657 | / | 920.997 |
| | = | 0.5783 |
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)) |
| = | (133.63 / (133.63 + 745.579)) | / | (143.695 / (143.695 + 759.571)) |
| = | 0.151989 | / | 0.159084 |
| | = | 0.9554 |
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) |
| = | (333.217 / 532.657) | / | (298.161 / 920.997) |
| = | 0.625575 | / | 0.323737 |
| | = | 1.9324 |
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) |
| = | ((372.039 + 216.852) / 1114.005) | / | ((121.715 + 792.334) / 1431.79) |
| = | 0.528625 | / | 0.638396 |
| | = | 0.8281 |
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 |
| = | (15.598 - 127.618 | - | 115.326) | / | 1114.005 |
| | = | -0.20408 |
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.
W&T Offshore has a M-score of -3.38 suggests that the company is unlikely to be a manipulator.
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