UPL Beneish M-Score Historical Data
The historical data trend for UPL'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.
UPL Beneish M-Score Chart
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UPL 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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-1.15 |
-2.73 |
-2.71 |
-2.48 |
-2.55 |
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UPL Quarterly Data
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Dec23 |
| Beneish M-Score |
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-2.55 |
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Competitive Comparison of UPL's Beneish M-Score
For the Agricultural Inputs subindustry, UPL'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.
UPL's Beneish M-Score Distribution in the Agriculture Industry
For the Agriculture industry and Basic Materials sector, UPL's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where UPL's Beneish M-Score falls into.
UPL 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 UPL 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 * 0.9637 | + | 0.528 * 1.0685 | + | 0.404 * 1.0053 | + | 0.892 * 1.1558 | + | 0.115 * 1.0211 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1085 | + | 4.679 * -0.047202 | - | 0.327 * 0.9269 |
| = | -2.55 |
* 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 ₹206,870 Mil.
Revenue was ₹531,340 Mil.
Gross Profit was ₹255,130 Mil.
Total Current Assets was ₹420,280 Mil.
Total Assets was ₹885,770 Mil.
Property, Plant and Equipment(Net PPE) was ₹102,660 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹25,470 Mil.
Selling, General, & Admin. Expense(SGA) was ₹23,600 Mil.
Total Current Liabilities was ₹290,370 Mil.
Long-Term Debt & Capital Lease Obligation was ₹208,190 Mil.
Net Income was ₹35,700 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹77,510 Mil.
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Total Receivables was ₹185,730 Mil.
Revenue was ₹459,710 Mil.
Gross Profit was ₹235,850 Mil.
Total Current Assets was ₹397,280 Mil.
Total Assets was ₹826,790 Mil.
Property, Plant and Equipment(Net PPE) was ₹92,630 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹23,590 Mil.
Selling, General, & Admin. Expense(SGA) was ₹18,420 Mil.
Total Current Liabilities was ₹279,760 Mil.
Long-Term Debt & Capital Lease Obligation was ₹222,310 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) |
| = | (206870 / 531340) | / | (185730 / 459710) |
| = | 0.389336 | / | 0.404016 |
| | = | 0.9637 |
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) |
| = | (235850 / 459710) | / | (255130 / 531340) |
| = | 0.513041 | / | 0.480163 |
| | = | 1.0685 |
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 - (420280 + 102660) / 885770) | / | (1 - (397280 + 92630) / 826790) |
| = | 0.409621 | / | 0.407455 |
| | = | 1.0053 |
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 |
| = | 531340 | / | 459710 |
| | = | 1.1558 |
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)) |
| = | (23590 / (23590 + 92630)) | / | (25470 / (25470 + 102660)) |
| = | 0.202977 | / | 0.198782 |
| | = | 1.0211 |
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) |
| = | (23600 / 531340) | / | (18420 / 459710) |
| = | 0.044416 | / | 0.040069 |
| | = | 1.1085 |
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) |
| = | ((208190 + 290370) / 885770) | / | ((222310 + 279760) / 826790) |
| = | 0.562855 | / | 0.607252 |
| | = | 0.9269 |
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 |
| = | (35700 - 0 | - | 77510) | / | 885770 |
| | = | -0.047202 |
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.
UPL has a M-score of -2.55 suggests that the company is unlikely to be a manipulator.
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