Optiemus Infracom Beneish M-Score Historical Data
The historical data trend for Optiemus Infracom'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.
Optiemus Infracom Beneish M-Score Chart
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Optiemus Infracom Annual Data
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Mar24 |
| Beneish M-Score |
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-2.08 |
-0.82 |
-1.47 |
-2.00 |
-2.37 |
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Optiemus Infracom Quarterly Data
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| Beneish M-Score |
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-2.37 |
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Competitive Comparison of Optiemus Infracom's Beneish M-Score
For the Electronics & Computer Distribution subindustry, Optiemus Infracom'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.
Optiemus Infracom's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Optiemus Infracom's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Optiemus Infracom's Beneish M-Score falls into.
Optiemus Infracom 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 Optiemus Infracom 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 * 1.0739 | + | 0.528 * 0.7373 | + | 0.404 * 0.663 | + | 0.892 * 1.2931 | + | 0.115 * 0.9494 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6738 | + | 4.679 * 0.012185 | - | 0.327 * 1.1717 |
| = | -2.37 |
* 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 ₹5,724 Mil.
Revenue was ₹14,767 Mil.
Gross Profit was ₹1,682 Mil.
Total Current Assets was ₹10,201 Mil.
Total Assets was ₹13,477 Mil.
Property, Plant and Equipment(Net PPE) was ₹1,986 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹176 Mil.
Selling, General, & Admin. Expense(SGA) was ₹71 Mil.
Total Current Liabilities was ₹8,471 Mil.
Long-Term Debt & Capital Lease Obligation was ₹672 Mil.
Net Income was ₹568 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹403 Mil.
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Total Receivables was ₹4,122 Mil.
Revenue was ₹11,420 Mil.
Gross Profit was ₹959 Mil.
Total Current Assets was ₹6,253 Mil.
Total Assets was ₹9,113 Mil.
Property, Plant and Equipment(Net PPE) was ₹1,543 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹130 Mil.
Selling, General, & Admin. Expense(SGA) was ₹82 Mil.
Total Current Liabilities was ₹4,653 Mil.
Long-Term Debt & Capital Lease Obligation was ₹623 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) |
| = | (5724.335 / 14767.327) | / | (4122.164 / 11419.665) |
| = | 0.387635 | / | 0.360971 |
| | = | 1.0739 |
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) |
| = | (958.713 / 11419.665) | / | (1681.553 / 14767.327) |
| = | 0.083953 | / | 0.11387 |
| | = | 0.7373 |
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 - (10200.666 + 1985.511) / 13477.042) | / | (1 - (6253.447 + 1543.481) / 9113.472) |
| = | 0.095783 | / | 0.144461 |
| | = | 0.663 |
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 |
| = | 14767.327 | / | 11419.665 |
| | = | 1.2931 |
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)) |
| = | (129.663 / (129.663 + 1543.481)) | / | (176.478 / (176.478 + 1985.511)) |
| = | 0.077497 | / | 0.081628 |
| | = | 0.9494 |
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) |
| = | (71.156 / 14767.327) | / | (81.662 / 11419.665) |
| = | 0.004818 | / | 0.007151 |
| | = | 0.6738 |
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) |
| = | ((671.929 + 8470.931) / 13477.042) | / | ((623.37 + 4653.459) / 9113.472) |
| = | 0.678403 | / | 0.579014 |
| | = | 1.1717 |
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 |
| = | (567.596 - 0 | - | 403.373) | / | 13477.042 |
| | = | 0.012185 |
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.
Optiemus Infracom has a M-score of -2.37 suggests that the company is unlikely to be a manipulator.
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