Sat Industries Beneish M-Score Historical Data
The historical data trend for Sat Industries'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.
Sat Industries Beneish M-Score Chart
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Sat Industries Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-3.02 |
-2.35 |
-1.84 |
-1.63 |
0.48 |
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Sat Industries Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
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Mar21 |
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Dec21 |
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Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.63 |
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0.48 |
Competitive Comparison of Sat Industries's Beneish M-Score
For the Steel subindustry, Sat Industries'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.
Sat Industries's Beneish M-Score Distribution in the Steel Industry
For the Steel industry and Basic Materials sector, Sat Industries's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sat Industries's Beneish M-Score falls into.
Sat Industries 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 Sat Industries 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 * 1.2244 | + | 0.528 * 0.8934 | + | 0.404 * 0.8852 | + | 0.892 * 1.0737 | + | 0.115 * 1.0442 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * 0.559315 | - | 0.327 * 0.4984 |
| = | 0.48 |
* 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 ₹2,111 Mil.
Revenue was ₹5,006 Mil.
Gross Profit was ₹1,794 Mil.
Total Current Assets was ₹6,878 Mil.
Total Assets was ₹8,933 Mil.
Property, Plant and Equipment(Net PPE) was ₹1,443 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹92 Mil.
Selling, General, & Admin. Expense(SGA) was ₹0 Mil.
Total Current Liabilities was ₹1,528 Mil.
Long-Term Debt & Capital Lease Obligation was ₹102 Mil.
Net Income was ₹2,579 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹-2,417 Mil.
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Total Receivables was ₹1,606 Mil.
Revenue was ₹4,662 Mil.
Gross Profit was ₹1,493 Mil.
Total Current Assets was ₹3,445 Mil.
Total Assets was ₹4,903 Mil.
Property, Plant and Equipment(Net PPE) was ₹1,079 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹72 Mil.
Selling, General, & Admin. Expense(SGA) was ₹0 Mil.
Total Current Liabilities was ₹1,512 Mil.
Long-Term Debt & Capital Lease Obligation was ₹283 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) |
| = | (2111.039 / 5006.228) | / | (1605.683 / 4662.397) |
| = | 0.421683 | / | 0.34439 |
| | = | 1.2244 |
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) |
| = | (1492.569 / 4662.397) | / | (1793.9 / 5006.228) |
| = | 0.320129 | / | 0.358334 |
| | = | 0.8934 |
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 - (6878.208 + 1442.722) / 8932.72) | / | (1 - (3444.958 + 1078.696) / 4902.998) |
| = | 0.068489 | / | 0.07737 |
| | = | 0.8852 |
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 |
| = | 5006.228 | / | 4662.397 |
| | = | 1.0737 |
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)) |
| = | (71.715 / (71.715 + 1078.696)) | / | (91.601 / (91.601 + 1442.722)) |
| = | 0.062339 | / | 0.059701 |
| | = | 1.0442 |
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) |
| = | (0 / 5006.228) | / | (0 / 4662.397) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((101.652 + 1527.729) / 8932.72) | / | ((282.713 + 1511.584) / 4902.998) |
| = | 0.182406 | / | 0.365959 |
| | = | 0.4984 |
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 |
| = | (2579.161 - 0 | - | -2417.045) | / | 8932.72 |
| | = | 0.559315 |
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.
Sat Industries has a M-score of 0.48 signals that the company is likely to be a manipulator.
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