Himalaya Shipping Beneish M-Score Historical Data
The historical data trend for Himalaya Shipping'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.
Himalaya Shipping Beneish M-Score Chart
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Himalaya Shipping Annual Data
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Trend |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
-1.43 |
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Himalaya Shipping Quarterly Data
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Jun21 |
Dec21 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
- |
-1.43 |
Competitive Comparison of Himalaya Shipping's Beneish M-Score
For the Marine Shipping subindustry, Himalaya Shipping'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.
Himalaya Shipping's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, Himalaya Shipping's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Himalaya Shipping's Beneish M-Score falls into.
Himalaya Shipping 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 Himalaya Shipping 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 * 0.4815 | + | 0.528 * 0.8671 | + | 0.404 * 0.0429 | + | 0.892 * 3.4016 | + | 0.115 * 0.5578 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.3869 | + | 4.679 * -0.037973 | - | 0.327 * 1.1098 |
| = | -1.43 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was kr14 Mil.
Revenue was 332.101 + 416.395 + 331.222 + 250.244 = kr1,330 Mil.
Gross Profit was 168.373 + 265.374 + 199.325 + 136.779 = kr770 Mil.
Total Current Assets was kr301 Mil.
Total Assets was kr9,875 Mil.
Property, Plant and Equipment(Net PPE) was kr9,571 Mil.
Depreciation, Depletion and Amortization(DDA) was kr285 Mil.
Selling, General, & Admin. Expense(SGA) was kr54 Mil.
Total Current Liabilities was kr402 Mil.
Long-Term Debt & Capital Lease Obligation was kr7,737 Mil.
Net Income was 11.445 + 113.333 + 72.853 + 26.445 = kr224 Mil.
Non Operating Income was -0.112 + -0.011 + 0 + 0 = kr-0 Mil.
Cash Flow from Operations was 117.837 + 175.475 + 187.319 + 118.558 = kr599 Mil.
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Total Receivables was kr9 Mil.
Revenue was 193.276 + 109.832 + 72.681 + 15.188 = kr391 Mil.
Gross Profit was 115.221 + 42.062 + 30.662 + 8.299 = kr196 Mil.
Total Current Assets was kr346 Mil.
Total Assets was kr6,321 Mil.
Property, Plant and Equipment(Net PPE) was kr5,921 Mil.
Depreciation, Depletion and Amortization(DDA) was kr97 Mil.
Selling, General, & Admin. Expense(SGA) was kr41 Mil.
Total Current Liabilities was kr267 Mil.
Long-Term Debt & Capital Lease Obligation was kr4,428 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) |
| = | (14.014 / 1329.962) | / | (8.556 / 390.977) |
| = | 0.010537 | / | 0.021884 |
| | = | 0.4815 |
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) |
| = | (196.244 / 390.977) | / | (769.851 / 1329.962) |
| = | 0.501932 | / | 0.578852 |
| | = | 0.8671 |
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 - (300.684 + 9570.766) / 9875.085) | / | (1 - (346.094 + 5920.988) / 6321.264) |
| = | 0.000368 | / | 0.008571 |
| | = | 0.0429 |
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 |
| = | 1329.962 | / | 390.977 |
| | = | 3.4016 |
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)) |
| = | (97.226 / (97.226 + 5920.988)) | / | (285.481 / (285.481 + 9570.766)) |
| = | 0.016155 | / | 0.028964 |
| | = | 0.5578 |
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) |
| = | (54.022 / 1329.962) | / | (41.049 / 390.977) |
| = | 0.040619 | / | 0.104991 |
| | = | 0.3869 |
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) |
| = | ((7737.397 + 401.679) / 9875.085) | / | ((4427.594 + 266.9) / 6321.264) |
| = | 0.824203 | / | 0.742651 |
| | = | 1.1098 |
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 |
| = | (224.076 - -0.123 | - | 599.189) | / | 9875.085 |
| | = | -0.037973 |
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.
Himalaya Shipping has a M-score of -1.43 signals that the company is likely to be a manipulator.
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