Rumo Beneish M-Score Historical Data
The historical data trend for Rumo'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.
Rumo Beneish M-Score Chart
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Rumo Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.06 |
-2.61 |
-2.69 |
-2.74 |
-3.05 |
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Rumo 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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-2.74 |
-2.82 |
-3.04 |
-2.97 |
-3.05 |
Competitive Comparison of Rumo's Beneish M-Score
For the Railroads subindustry, Rumo'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.
Rumo's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, Rumo's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Rumo's Beneish M-Score falls into.
Rumo 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 Rumo 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 * 0.8768 | + | 0.528 * 0.853 | + | 0.404 * 0.9897 | + | 0.892 * 1.1114 | + | 0.115 * 0.982 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0826 | + | 4.679 * -0.096085 | - | 0.327 * 1.0143 |
| = | -3.05 |
* 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$597 Mil.
Revenue was 2615.704 + 3175.072 + 2763.112 + 2383.828 = R$10,938 Mil.
Gross Profit was 809.728 + 1437.549 + 1071.774 + 780.233 = R$4,099 Mil.
Total Current Assets was R$10,252 Mil.
Total Assets was R$49,238 Mil.
Property, Plant and Equipment(Net PPE) was R$26,880 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,176 Mil.
Selling, General, & Admin. Expense(SGA) was R$601 Mil.
Total Current Liabilities was R$5,478 Mil.
Long-Term Debt & Capital Lease Obligation was R$23,820 Mil.
Net Income was -1.447 + 480.678 + 167.284 + 73.393 = R$720 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = R$0 Mil.
Cash Flow from Operations was 1104.772 + 1756.633 + 1652.805 + 936.786 = R$5,451 Mil.
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Total Receivables was R$613 Mil.
Revenue was 2219.916 + 2950.6 + 2464.63 + 2206.362 = R$9,842 Mil.
Gross Profit was 585.228 + 1121.585 + 807.048 + 632.499 = R$3,146 Mil.
Total Current Assets was R$9,755 Mil.
Total Assets was R$45,952 Mil.
Property, Plant and Equipment(Net PPE) was R$24,781 Mil.
Depreciation, Depletion and Amortization(DDA) was R$1,967 Mil.
Selling, General, & Admin. Expense(SGA) was R$499 Mil.
Total Current Liabilities was R$5,690 Mil.
Long-Term Debt & Capital Lease Obligation was R$21,266 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) |
| = | (597.054 / 10937.716) | / | (612.693 / 9841.508) |
| = | 0.054587 | / | 0.062256 |
| | = | 0.8768 |
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) |
| = | (3146.36 / 9841.508) | / | (4099.284 / 10937.716) |
| = | 0.319703 | / | 0.374784 |
| | = | 0.853 |
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 - (10251.83 + 26880.14) / 49238.436) | / | (1 - (9754.895 + 24781.472) / 45951.745) |
| = | 0.245874 | / | 0.248421 |
| | = | 0.9897 |
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 |
| = | 10937.716 | / | 9841.508 |
| | = | 1.1114 |
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)) |
| = | (1966.945 / (1966.945 + 24781.472)) | / | (2175.834 / (2175.834 + 26880.14)) |
| = | 0.073535 | / | 0.074884 |
| | = | 0.982 |
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) |
| = | (600.63 / 10937.716) | / | (499.193 / 9841.508) |
| = | 0.054914 | / | 0.050723 |
| | = | 1.0826 |
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) |
| = | ((23819.76 + 5477.537) / 49238.436) | / | ((21266.326 + 5690.421) / 45951.745) |
| = | 0.595009 | / | 0.586632 |
| | = | 1.0143 |
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 |
| = | (719.908 - 0 | - | 5450.996) | / | 49238.436 |
| | = | -0.096085 |
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.
Rumo has a M-score of -3.05 suggests that the company is unlikely to be a manipulator.
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