Tupy Beneish M-Score Historical Data
The historical data trend for Tupy'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.
Tupy Beneish M-Score Chart
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Tupy Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.88 |
-2.76 |
-2.02 |
-1.98 |
-2.61 |
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Tupy 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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-1.98 |
-2.14 |
-2.43 |
-2.36 |
-2.61 |
Competitive Comparison of Tupy's Beneish M-Score
For the Metal Fabrication subindustry, Tupy'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.
Tupy's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Tupy's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Tupy's Beneish M-Score falls into.
Tupy 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 Tupy 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 * 0.8073 | + | 0.528 * 1.0895 | + | 0.404 * 1.0551 | + | 0.892 * 1.1169 | + | 0.115 * 1.0243 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9687 | + | 4.679 * -0.03121 | - | 0.327 * 0.9582 |
| = | -2.61 |
* 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$1,832 Mil.
Revenue was 2621.978 + 2975.942 + 2965.864 + 2804.406 = R$11,368 Mil.
Gross Profit was 414.454 + 522.539 + 493.43 + 504.7 = R$1,935 Mil.
Total Current Assets was R$6,187 Mil.
Total Assets was R$10,285 Mil.
Property, Plant and Equipment(Net PPE) was R$2,793 Mil.
Depreciation, Depletion and Amortization(DDA) was R$367 Mil.
Selling, General, & Admin. Expense(SGA) was R$1,028 Mil.
Total Current Liabilities was R$3,247 Mil.
Long-Term Debt & Capital Lease Obligation was R$3,128 Mil.
Net Income was 157.148 + 148.849 + 59.903 + 142.239 = R$508 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = R$0 Mil.
Cash Flow from Operations was 443.315 + 358.57 + 159.142 + -131.902 = R$829 Mil.
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Total Receivables was R$2,031 Mil.
Revenue was 2591.09 + 2694.013 + 2529.016 + 2364.297 = R$10,178 Mil.
Gross Profit was 433 + 535.082 + 509.922 + 409.639 = R$1,888 Mil.
Total Current Assets was R$6,427 Mil.
Total Assets was R$10,243 Mil.
Property, Plant and Equipment(Net PPE) was R$2,584 Mil.
Depreciation, Depletion and Amortization(DDA) was R$349 Mil.
Selling, General, & Admin. Expense(SGA) was R$950 Mil.
Total Current Liabilities was R$3,390 Mil.
Long-Term Debt & Capital Lease Obligation was R$3,236 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) |
| = | (1831.735 / 11368.19) | / | (2031.38 / 10178.416) |
| = | 0.161128 | / | 0.199577 |
| | = | 0.8073 |
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) |
| = | (1887.643 / 10178.416) | / | (1935.123 / 11368.19) |
| = | 0.185455 | / | 0.170223 |
| | = | 1.0895 |
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 - (6186.653 + 2792.713) / 10284.745) | / | (1 - (6426.68 + 2584.302) / 10243.258) |
| = | 0.126924 | / | 0.120301 |
| | = | 1.0551 |
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 |
| = | 11368.19 | / | 10178.416 |
| | = | 1.1169 |
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)) |
| = | (348.551 / (348.551 + 2584.302)) | / | (366.54 / (366.54 + 2792.713)) |
| = | 0.118844 | / | 0.116021 |
| | = | 1.0243 |
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) |
| = | (1028.15 / 11368.19) | / | (950.285 / 10178.416) |
| = | 0.090441 | / | 0.093363 |
| | = | 0.9687 |
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) |
| = | ((3127.748 + 3246.79) / 10284.745) | / | ((3235.576 + 3390.345) / 10243.258) |
| = | 0.619805 | / | 0.646857 |
| | = | 0.9582 |
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 |
| = | (508.139 - 0 | - | 829.125) | / | 10284.745 |
| | = | -0.03121 |
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.
Tupy has a M-score of -2.61 suggests that the company is unlikely to be a manipulator.
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