Cargosol Logistics Beneish M-Score Historical Data
The historical data trend for Cargosol Logistics'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.
Cargosol Logistics Beneish M-Score Chart
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Cargosol Logistics Annual Data
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Trend |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
|
- |
- |
-2.22 |
-2.23 |
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Cargosol Logistics Semi-Annual Data
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|
Mar20 |
Mar21 |
Mar22 |
Sep22 |
Mar23 |
Sep23 |
| Beneish M-Score |
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- |
-2.22 |
- |
-2.23 |
- |
Competitive Comparison of Cargosol Logistics's Beneish M-Score
For the Integrated Freight & Logistics subindustry, Cargosol Logistics'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.
Cargosol Logistics's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, Cargosol Logistics's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cargosol Logistics's Beneish M-Score falls into.
Cargosol Logistics 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 Cargosol Logistics 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 * 1.3799 | + | 0.528 * 1.022 | + | 0.404 * 0.3963 | + | 0.892 * 0.848 | + | 0.115 * 0.9714 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.8687 | + | 4.679 * 0.076651 | - | 0.327 * 0.8021 |
| = | -2.23 |
* 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 (Mar23) TTM: | Last Year (Mar22) TTM: |
Total Receivables was ₹313 Mil.
Revenue was ₹1,699 Mil.
Gross Profit was ₹1,606 Mil.
Total Current Assets was ₹339 Mil.
Total Assets was ₹646 Mil.
Property, Plant and Equipment(Net PPE) was ₹251 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹37 Mil.
Selling, General, & Admin. Expense(SGA) was ₹23 Mil.
Total Current Liabilities was ₹261 Mil.
Long-Term Debt & Capital Lease Obligation was ₹111 Mil.
Net Income was ₹42 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹-7 Mil.
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Total Receivables was ₹267 Mil.
Revenue was ₹2,004 Mil.
Gross Profit was ₹1,936 Mil.
Total Current Assets was ₹359 Mil.
Total Assets was ₹578 Mil.
Property, Plant and Equipment(Net PPE) was ₹92 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹13 Mil.
Selling, General, & Admin. Expense(SGA) was ₹14 Mil.
Total Current Liabilities was ₹334 Mil.
Long-Term Debt & Capital Lease Obligation was ₹82 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) |
| = | (312.739 / 1699.396) | / | (267.253 / 2003.943) |
| = | 0.18403 | / | 0.133364 |
| | = | 1.3799 |
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) |
| = | (1935.735 / 2003.943) | / | (1606.2 / 1699.396) |
| = | 0.965963 | / | 0.945159 |
| | = | 1.022 |
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 - (338.74 + 250.617) / 645.794) | / | (1 - (358.849 + 91.87) / 578.234) |
| = | 0.087392 | / | 0.220525 |
| | = | 0.3963 |
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 |
| = | 1699.396 | / | 2003.943 |
| | = | 0.848 |
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)) |
| = | (13.189 / (13.189 + 91.87)) | / | (37.195 / (37.195 + 250.617)) |
| = | 0.125539 | / | 0.129234 |
| | = | 0.9714 |
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) |
| = | (22.633 / 1699.396) | / | (14.283 / 2003.943) |
| = | 0.013318 | / | 0.007127 |
| | = | 1.8687 |
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) |
| = | ((111.48 + 261.139) / 645.794) | / | ((81.7 + 334.243) / 578.234) |
| = | 0.576994 | / | 0.719333 |
| | = | 0.8021 |
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 |
| = | (42.06 - 0 | - | -7.441) | / | 645.794 |
| | = | 0.076651 |
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.
Cargosol Logistics has a M-score of -2.23 suggests that the company is unlikely to be a manipulator.
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