Sheetal Cool Products Beneish M-Score Historical Data
The historical data trend for Sheetal Cool Products'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.
Sheetal Cool Products Beneish M-Score Chart
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Sheetal Cool Products Annual Data
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Mar14 |
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Mar19 |
Mar20 |
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Mar23 |
| Beneish M-Score |
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-3.28 |
-1.35 |
-3.12 |
-0.14 |
-3.21 |
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Sheetal Cool Products Quarterly Data
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Mar15 |
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Dec23 |
| Beneish M-Score |
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-3.21 |
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Competitive Comparison of Sheetal Cool Products's Beneish M-Score
For the Packaged Foods subindustry, Sheetal Cool Products'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.
Sheetal Cool Products's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, Sheetal Cool Products's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sheetal Cool Products's Beneish M-Score falls into.
Sheetal Cool Products 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 Sheetal Cool Products 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 * 0.1687 | + | 0.528 * 0.8313 | + | 0.404 * 1.1045 | + | 0.892 * 1.0413 | + | 0.115 * 1.0398 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2238 | + | 4.679 * 0.012486 | - | 0.327 * 0.9512 |
| = | -3.21 |
* 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 ₹38 Mil.
Revenue was ₹3,403 Mil.
Gross Profit was ₹808 Mil.
Total Current Assets was ₹1,739 Mil.
Total Assets was ₹2,267 Mil.
Property, Plant and Equipment(Net PPE) was ₹490 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹96 Mil.
Selling, General, & Admin. Expense(SGA) was ₹45 Mil.
Total Current Liabilities was ₹980 Mil.
Long-Term Debt & Capital Lease Obligation was ₹239 Mil.
Net Income was ₹205 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹176 Mil.
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Total Receivables was ₹216 Mil.
Revenue was ₹3,268 Mil.
Gross Profit was ₹645 Mil.
Total Current Assets was ₹1,401 Mil.
Total Assets was ₹1,959 Mil.
Property, Plant and Equipment(Net PPE) was ₹529 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹109 Mil.
Selling, General, & Admin. Expense(SGA) was ₹35 Mil.
Total Current Liabilities was ₹796 Mil.
Long-Term Debt & Capital Lease Obligation was ₹311 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) |
| = | (37.91 / 3402.642) | / | (215.848 / 3267.683) |
| = | 0.011141 | / | 0.066055 |
| | = | 0.1687 |
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) |
| = | (645.215 / 3267.683) | / | (808.21 / 3402.642) |
| = | 0.197453 | / | 0.237524 |
| | = | 0.8313 |
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 - (1739.488 + 490.454) / 2267.294) | / | (1 - (1400.662 + 529.102) / 1958.984) |
| = | 0.016474 | / | 0.014916 |
| | = | 1.1045 |
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 |
| = | 3402.642 | / | 3267.683 |
| | = | 1.0413 |
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)) |
| = | (109.029 / (109.029 + 529.102)) | / | (96.437 / (96.437 + 490.454)) |
| = | 0.170857 | / | 0.164318 |
| | = | 1.0398 |
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) |
| = | (44.955 / 3402.642) | / | (35.277 / 3267.683) |
| = | 0.013212 | / | 0.010796 |
| | = | 1.2238 |
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) |
| = | ((239.004 + 980.063) / 2267.294) | / | ((311.158 + 796.174) / 1958.984) |
| = | 0.537675 | / | 0.565258 |
| | = | 0.9512 |
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 |
| = | (204.542 - 0 | - | 176.233) | / | 2267.294 |
| | = | 0.012486 |
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.
Sheetal Cool Products has a M-score of -3.21 suggests that the company is unlikely to be a manipulator.
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