Subsea 7 Beneish M-Score Historical Data
The historical data trend for Subsea 7'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.
Subsea 7 Beneish M-Score Chart
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Subsea 7 Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-5.48 |
-3.17 |
-2.91 |
-2.72 |
-3.03 |
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Subsea 7 Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-2.66 |
-3.07 |
-2.95 |
-3.03 |
-3.13 |
Competitive Comparison of Subsea 7's Beneish M-Score
For the Oil & Gas Equipment & Services subindustry, Subsea 7'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.
Subsea 7's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Subsea 7's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Subsea 7's Beneish M-Score falls into.
Subsea 7 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 Subsea 7 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 * 0.8606 | + | 0.528 * 0.5694 | + | 0.404 * 1.157 | + | 0.892 * 1.1517 | + | 0.115 * 0.8339 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0206 | + | 4.679 * -0.10516 | - | 0.327 * 0.9378 |
| = | -3.13 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was kr21,158 Mil.
Revenue was 16331.239 + 20967.561 + 19480.786 + 18459.119 = kr75,239 Mil.
Gross Profit was 1726.665 + 2247.446 + 2401.77 + 2090.172 = kr8,466 Mil.
Total Current Assets was kr28,869 Mil.
Total Assets was kr83,684 Mil.
Property, Plant and Equipment(Net PPE) was kr45,842 Mil.
Depreciation, Depletion and Amortization(DDA) was kr6,907 Mil.
Selling, General, & Admin. Expense(SGA) was kr3,404 Mil.
Total Current Liabilities was kr27,799 Mil.
Long-Term Debt & Capital Lease Obligation was kr7,870 Mil.
Net Income was 203.954 + 246.849 + 991.089 + 627.37 = kr2,069 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = kr0 Mil.
Cash Flow from Operations was 545.656 + 5463.213 + 2872.351 + 1988.264 = kr10,869 Mil.
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Total Receivables was kr21,346 Mil.
Revenue was 14808.124 + 17209.236 + 16925.722 + 16386.776 = kr65,330 Mil.
Gross Profit was 863.825 + 1196.302 + 1371.689 + 753.589 = kr4,185 Mil.
Total Current Assets was kr30,225 Mil.
Total Assets was kr86,823 Mil.
Property, Plant and Equipment(Net PPE) was kr48,550 Mil.
Depreciation, Depletion and Amortization(DDA) was kr5,951 Mil.
Selling, General, & Admin. Expense(SGA) was kr2,896 Mil.
Total Current Liabilities was kr28,206 Mil.
Long-Term Debt & Capital Lease Obligation was kr11,254 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) |
| = | (21157.785 / 75238.705) | / | (21346.239 / 65329.858) |
| = | 0.281209 | / | 0.326746 |
| | = | 0.8606 |
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) |
| = | (4185.405 / 65329.858) | / | (8466.053 / 75238.705) |
| = | 0.064066 | / | 0.112523 |
| | = | 0.5694 |
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 - (28868.514 + 45841.513) / 83683.986) | / | (1 - (30225.383 + 48550.357) / 86822.896) |
| = | 0.107236 | / | 0.092685 |
| | = | 1.157 |
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 |
| = | 75238.705 | / | 65329.858 |
| | = | 1.1517 |
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)) |
| = | (5951.264 / (5951.264 + 48550.357)) | / | (6906.987 / (6906.987 + 45841.513)) |
| = | 0.109194 | / | 0.130942 |
| | = | 0.8339 |
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) |
| = | (3403.978 / 75238.705) | / | (2895.966 / 65329.858) |
| = | 0.045242 | / | 0.044328 |
| | = | 1.0206 |
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) |
| = | ((7869.833 + 27798.558) / 83683.986) | / | ((11254.132 + 28205.901) / 86822.896) |
| = | 0.426227 | / | 0.454489 |
| | = | 0.9378 |
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 |
| = | (2069.262 - 0 | - | 10869.484) | / | 83683.986 |
| | = | -0.10516 |
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.
Subsea 7 has a M-score of -3.13 suggests that the company is unlikely to be a manipulator.
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