Seadrill Beneish M-Score Historical Data
The historical data trend for Seadrill'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.
Seadrill Beneish M-Score Chart
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Seadrill Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
- |
-2.27 |
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Seadrill Quarterly Data
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Dec19 |
Dec20 |
Jun21 |
Sep21 |
Dec21 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.48 |
-2.27 |
-2.15 |
-2.73 |
-2.38 |
Competitive Comparison of Seadrill's Beneish M-Score
For the Oil & Gas Drilling subindustry, Seadrill'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.
Seadrill's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Seadrill's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Seadrill's Beneish M-Score falls into.
Seadrill 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 Seadrill 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 * 0.5531 | + | 0.528 * 1.2689 | + | 0.404 * 1.4667 | + | 0.892 * 1.3611 | + | 0.115 * 0.6981 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.5481 | + | 4.679 * 0.001804 | - | 0.327 * 1.0991 |
| = | -2.39 |
* 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 kr2,018 Mil.
Revenue was 3760.4 + 3980.775 + 3894.641 + 4304.155 = kr15,940 Mil.
Gross Profit was 807.318 + 1188.925 + 965.701 + 854.501 = kr3,816 Mil.
Total Current Assets was kr11,016 Mil.
Total Assets was kr44,105 Mil.
Property, Plant and Equipment(Net PPE) was kr30,625 Mil.
Depreciation, Depletion and Amortization(DDA) was kr1,759 Mil.
Selling, General, & Admin. Expense(SGA) was kr1,081 Mil.
Total Current Liabilities was kr4,355 Mil.
Long-Term Debt & Capital Lease Obligation was kr6,480 Mil.
Net Income was 339.923 + 2685.696 + 636.726 + 770.106 = kr4,432 Mil.
Non Operating Income was -42.49 + 1963.849 + 21.224 + 73.846 = kr2,016 Mil.
Cash Flow from Operations was -286.81 + 838.617 + 307.751 + 1476.916 = kr2,336 Mil.
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Total Receivables was kr2,681 Mil.
Revenue was 4440.026 + 4469.71 + 2801.592 + 0 = kr11,711 Mil.
Gross Profit was 1415.66 + 1468.31 + 674.067 + 0 = kr3,558 Mil.
Total Current Assets was kr14,317 Mil.
Total Assets was kr46,449 Mil.
Property, Plant and Equipment(Net PPE) was kr30,362 Mil.
Depreciation, Depletion and Amortization(DDA) was kr1,197 Mil.
Selling, General, & Admin. Expense(SGA) was kr513 Mil.
Total Current Liabilities was kr3,839 Mil.
Long-Term Debt & Capital Lease Obligation was kr6,542 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) |
| = | (2018.294 / 15939.971) | / | (2681.175 / 11711.328) |
| = | 0.126618 | / | 0.228939 |
| | = | 0.5531 |
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) |
| = | (3558.037 / 11711.328) | / | (3816.445 / 15939.971) |
| = | 0.303812 | / | 0.239426 |
| | = | 1.2689 |
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 - (11015.636 + 30624.956) / 44105.035) | / | (1 - (14317.475 + 30361.626) / 46448.676) |
| = | 0.055877 | / | 0.038097 |
| | = | 1.4667 |
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 |
| = | 15939.971 | / | 11711.328 |
| | = | 1.3611 |
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)) |
| = | (1196.893 / (1196.893 + 30361.626)) | / | (1759.495 / (1759.495 + 30624.956)) |
| = | 0.037926 | / | 0.054331 |
| | = | 0.6981 |
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) |
| = | (1081.166 / 15939.971) | / | (513.096 / 11711.328) |
| = | 0.067827 | / | 0.043812 |
| | = | 1.5481 |
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) |
| = | ((6479.786 + 4355.266) / 44105.035) | / | ((6542.067 + 3839.443) / 46448.676) |
| = | 0.245665 | / | 0.223505 |
| | = | 1.0991 |
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 |
| = | (4432.451 - 2016.429 | - | 2336.474) | / | 44105.035 |
| | = | 0.001804 |
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.
Seadrill has a M-score of -2.39 suggests that the company is unlikely to be a manipulator.
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