TORM Beneish M-Score Historical Data
The historical data trend for TORM'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.
TORM Beneish M-Score Chart
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TORM Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1,165.85 |
-3.17 |
-1.98 |
-0.67 |
-3.15 |
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TORM Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.94 |
-3.15 |
-2.79 |
-2.94 |
-3.06 |
Competitive Comparison of TORM's Beneish M-Score
For the Oil & Gas Midstream subindustry, TORM'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.
TORM's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, TORM's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where TORM's Beneish M-Score falls into.
TORM 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 TORM 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 * 0.7084 | + | 0.528 * 1.0348 | + | 0.404 * 1.0836 | + | 0.892 * 1.0197 | + | 0.115 * 1.0209 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2596 | + | 4.679 * -0.077574 | - | 0.327 * 0.9204 |
| = | -3.06 |
* 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 €198 Mil.
Revenue was 335.262 + 406.623 + 408.572 + 355.606 = €1,506 Mil.
Gross Profit was 195.247 + 260.585 + 265.604 + 209.139 = €931 Mil.
Total Current Assets was €626 Mil.
Total Assets was €3,077 Mil.
Property, Plant and Equipment(Net PPE) was €2,441 Mil.
Depreciation, Depletion and Amortization(DDA) was €163 Mil.
Selling, General, & Admin. Expense(SGA) was €89 Mil.
Total Current Liabilities was €253 Mil.
Long-Term Debt & Capital Lease Obligation was €940 Mil.
Net Income was 117.581 + 180.412 + 192.464 + 169.246 = €660 Mil.
Non Operating Income was 10.001 + 9.755 + 15.64 + 36.567 = €72 Mil.
Cash Flow from Operations was 214.168 + 261.792 + 171.672 + 178.769 = €826 Mil.
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Total Receivables was €275 Mil.
Revenue was 335.54 + 354.709 + 364.447 + 422.299 = €1,477 Mil.
Gross Profit was 193.491 + 252.164 + 217.715 + 280.991 = €944 Mil.
Total Current Assets was €633 Mil.
Total Assets was €2,631 Mil.
Property, Plant and Equipment(Net PPE) was €1,991 Mil.
Depreciation, Depletion and Amortization(DDA) was €136 Mil.
Selling, General, & Admin. Expense(SGA) was €69 Mil.
Total Current Liabilities was €271 Mil.
Long-Term Debt & Capital Lease Obligation was €837 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) |
| = | (198.31 / 1506.063) | / | (274.541 / 1476.995) |
| = | 0.131674 | / | 0.185878 |
| | = | 0.7084 |
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) |
| = | (944.361 / 1476.995) | / | (930.575 / 1506.063) |
| = | 0.63938 | / | 0.617886 |
| | = | 1.0348 |
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 - (625.835 + 2440.629) / 3076.555) | / | (1 - (632.569 + 1990.657) / 2631.19) |
| = | 0.00328 | / | 0.003027 |
| | = | 1.0836 |
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 |
| = | 1506.063 | / | 1476.995 |
| | = | 1.0197 |
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)) |
| = | (136.26 / (136.26 + 1990.657)) | / | (163.411 / (163.411 + 2440.629)) |
| = | 0.064065 | / | 0.062753 |
| | = | 1.0209 |
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) |
| = | (88.981 / 1506.063) | / | (69.281 / 1476.995) |
| = | 0.059082 | / | 0.046907 |
| | = | 1.2596 |
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) |
| = | ((940.284 + 253.001) / 3076.555) | / | ((837.491 + 271.262) / 2631.19) |
| = | 0.387864 | / | 0.421388 |
| | = | 0.9204 |
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 |
| = | (659.703 - 71.963 | - | 826.401) | / | 3076.555 |
| | = | -0.077574 |
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.
TORM has a M-score of -3.06 suggests that the company is unlikely to be a manipulator.
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