Cube Highways Trust Beneish M-Score Historical Data
The historical data trend for Cube Highways Trust'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.
Cube Highways Trust Beneish M-Score Chart
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Cube Highways Trust Annual Data
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Trend |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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- |
- |
-3.33 |
- |
- |
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Cube Highways Trust Semi-Annual Data
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Mar20 |
Mar21 |
Mar22 |
Sep22 |
Mar23 |
Sep23 |
Mar24 |
Sep24 |
| Beneish M-Score |
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Competitive Comparison of Cube Highways Trust's Beneish M-Score
For the Infrastructure Operations subindustry, Cube Highways Trust'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.
Cube Highways Trust's Beneish M-Score Distribution in the Construction Industry
For the Construction industry and Industrials sector, Cube Highways Trust's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cube Highways Trust's Beneish M-Score falls into.
Cube Highways Trust 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 Cube Highways Trust 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 * | + | 0.528 * | + | 0.404 * | + | 0.892 * | + | 0.115 * |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * | + | 4.679 * | - | 0.327 * |
| = | |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₹1,560 Mil.
Revenue was ₹29,056 Mil.
Gross Profit was ₹19,090 Mil.
Total Current Assets was ₹22,774 Mil.
Total Assets was ₹246,258 Mil.
Property, Plant and Equipment(Net PPE) was ₹265 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹11,826 Mil.
Selling, General, & Admin. Expense(SGA) was ₹576 Mil.
Total Current Liabilities was ₹11,302 Mil.
Long-Term Debt & Capital Lease Obligation was ₹102,630 Mil.
Net Income was ₹-7,059 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹18,699 Mil.
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Total Receivables was ₹0 Mil.
Revenue was ₹0 Mil.
Gross Profit was ₹-275 Mil.
Total Current Assets was ₹0 Mil.
Total Assets was ₹0 Mil.
Property, Plant and Equipment(Net PPE) was ₹0 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹0 Mil.
Selling, General, & Admin. Expense(SGA) was ₹1 Mil.
Total Current Liabilities was ₹290 Mil.
Long-Term Debt & Capital Lease Obligation was ₹0 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) |
| = | (1560.26 / 29055.69) | / | (0 / 0) |
| = | 0.053699 | / | |
| | = | |
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) |
| = | (-274.82 / 0) | / | (19089.59 / 29055.69) |
| = | | / | 0.657 |
| | = | |
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 - (22774.29 + 264.99) / 246257.52) | / | (1 - (0.24 + 0) / 0.24) |
| = | 0.906442 | / | 0 |
| | = | |
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 |
| = | 29055.69 | / | 0 |
| | = | |
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)) |
| = | (0 / (0 + 0)) | / | (11825.72 / (11825.72 + 264.99)) |
| = | | / | 0.978083 |
| | = | |
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) |
| = | (576.35 / 29055.69) | / | (1.06 / 0) |
| = | 0.019836 | / | |
| | = | |
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) |
| = | ((102630.24 + 11302.43) / 246257.52) | / | ((0 + 290.2) / 0.24) |
| = | 0.462657 | / | 1209.166667 |
| | = | |
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 |
| = | (-7059.22 - 0 | - | 18699.46) | / | 246257.52 |
| | = | -0.104601 |
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.
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