Coty Beneish M-Score Historical Data
The historical data trend for Coty'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.
Coty Beneish M-Score Chart
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Coty Annual Data
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Trend |
Jun14 |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-3.17 |
-3.08 |
-2.35 |
-2.92 |
-2.66 |
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Coty Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.82 |
-2.79 |
-2.66 |
-2.54 |
-2.45 |
Competitive Comparison of Coty's Beneish M-Score
For the Household & Personal Products subindustry, Coty'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.
Coty's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, Coty's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Coty's Beneish M-Score falls into.
Coty 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 Coty 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 * 0.9773 | + | 0.528 * 1.0057 | + | 0.404 * 0.9609 | + | 0.892 * 1.1021 | + | 0.115 * 1.0246 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9369 | + | 4.679 * -0.030924 | - | 0.327 * 0.9025 |
| = | -2.52 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was R$2,451 Mil.
Revenue was 8464.894 + 8106.382 + 6560.261 + 6713.365 = R$29,845 Mil.
Gross Profit was 5507.865 + 5145.632 + 4123.218 + 4223.133 = R$19,000 Mil.
Total Current Assets was R$11,865 Mil.
Total Assets was R$63,774 Mil.
Property, Plant and Equipment(Net PPE) was R$4,879 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,132 Mil.
Selling, General, & Admin. Expense(SGA) was R$14,892 Mil.
Total Current Liabilities was R$13,969 Mil.
Long-Term Debt & Capital Lease Obligation was R$19,278 Mil.
Net Income was 886.374 + 7.902 + 159.687 + 564.612 = R$1,619 Mil.
Non Operating Income was 356.705 + -559.061 + 103.869 + 842.231 = R$744 Mil.
Cash Flow from Operations was 2067.226 + 919.586 + 509.153 + -648.992 = R$2,847 Mil.
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Total Receivables was R$2,275 Mil.
Revenue was 7991.891 + 7288.604 + 5897.228 + 5903.006 = R$27,081 Mil.
Gross Profit was 5236.483 + 4659.987 + 3644.944 + 3797.491 = R$17,339 Mil.
Total Current Assets was R$9,999 Mil.
Total Assets was R$65,329 Mil.
Property, Plant and Equipment(Net PPE) was R$5,194 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,351 Mil.
Selling, General, & Admin. Expense(SGA) was R$14,423 Mil.
Total Current Liabilities was R$15,293 Mil.
Long-Term Debt & Capital Lease Obligation was R$22,446 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) |
| = | (2450.88 / 29844.902) | / | (2275.455 / 27080.729) |
| = | 0.082121 | / | 0.084025 |
| | = | 0.9773 |
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) |
| = | (17338.905 / 27080.729) | / | (18999.848 / 29844.902) |
| = | 0.640267 | / | 0.63662 |
| | = | 1.0057 |
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 - (11865.356 + 4878.731) / 63774.327) | / | (1 - (9999.306 + 5193.995) / 65329.359) |
| = | 0.737448 | / | 0.767435 |
| | = | 0.9609 |
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 |
| = | 29844.902 | / | 27080.729 |
| | = | 1.1021 |
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)) |
| = | (2350.617 / (2350.617 + 5193.995)) | / | (2131.864 / (2131.864 + 4878.731)) |
| = | 0.311562 | / | 0.304092 |
| | = | 1.0246 |
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) |
| = | (14891.781 / 29844.902) | / | (14423.097 / 27080.729) |
| = | 0.498972 | / | 0.532596 |
| | = | 0.9369 |
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) |
| = | ((19278.263 + 13969.33) / 63774.327) | / | ((22446.116 + 15293.488) / 65329.359) |
| = | 0.521332 | / | 0.577682 |
| | = | 0.9025 |
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 |
| = | (1618.575 - 743.744 | - | 2846.973) | / | 63774.327 |
| | = | -0.030924 |
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.
Coty has a M-score of -2.52 suggests that the company is unlikely to be a manipulator.
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