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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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.97 |
-3.05 |
-2.93 |
-3.07 |
-3.19 |
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 * 0.926 | + | 0.528 * 0.8348 | + | 0.404 * 0.9172 | + | 0.892 * 1.2416 | + | 0.115 * 0.9493 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9462 | + | 4.679 * -0.15522 | - | 0.327 * 1.0472 |
| = | -3.19 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was R$796 Mil.
Revenue was 3752.263 + 3574.737 + 3146.017 + 2615.704 = R$13,089 Mil.
Gross Profit was 1866.08 + 1767.183 + 1319.984 + 809.728 = R$5,763 Mil.
Total Current Assets was R$11,630 Mil.
Total Assets was R$49,814 Mil.
Property, Plant and Equipment(Net PPE) was R$27,076 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,312 Mil.
Selling, General, & Admin. Expense(SGA) was R$664 Mil.
Total Current Liabilities was R$5,931 Mil.
Long-Term Debt & Capital Lease Obligation was R$24,981 Mil.
Net Income was 680.812 + -1744.323 + 368.977 + -1.447 = R$-696 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = R$0 Mil.
Cash Flow from Operations was 2202.448 + 2318.244 + 1410.681 + 1104.772 = R$7,036 Mil.
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Total Receivables was R$693 Mil.
Revenue was 3175.072 + 2763.112 + 2383.828 + 2219.916 = R$10,542 Mil.
Gross Profit was 1437.549 + 1071.774 + 780.233 + 585.228 = R$3,875 Mil.
Total Current Assets was R$11,464 Mil.
Total Assets was R$49,320 Mil.
Property, Plant and Equipment(Net PPE) was R$25,866 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,088 Mil.
Selling, General, & Admin. Expense(SGA) was R$565 Mil.
Total Current Liabilities was R$5,770 Mil.
Long-Term Debt & Capital Lease Obligation was R$23,457 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) |
| = | (796.224 / 13088.721) | / | (692.578 / 10541.928) |
| = | 0.060833 | / | 0.065697 |
| | = | 0.926 |
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) |
| = | (3874.784 / 10541.928) | / | (5762.975 / 13088.721) |
| = | 0.367559 | / | 0.440301 |
| | = | 0.8348 |
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 - (11630.021 + 27076.297) / 49813.935) | / | (1 - (11464.205 + 25865.682) / 49319.503) |
| = | 0.222982 | / | 0.243101 |
| | = | 0.9172 |
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 |
| = | 13088.721 | / | 10541.928 |
| | = | 1.2416 |
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)) |
| = | (2087.595 / (2087.595 + 25865.682)) | / | (2312.049 / (2312.049 + 27076.297)) |
| = | 0.074682 | / | 0.078672 |
| | = | 0.9493 |
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) |
| = | (663.716 / 13088.721) | / | (564.964 / 10541.928) |
| = | 0.050709 | / | 0.053592 |
| | = | 0.9462 |
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) |
| = | ((24981.293 + 5931.198) / 49813.935) | / | ((23457.08 + 5770.255) / 49319.503) |
| = | 0.620559 | / | 0.592612 |
| | = | 1.0472 |
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 |
| = | (-695.981 - 0 | - | 7036.145) | / | 49813.935 |
| | = | -0.15522 |
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 -3.19 suggests that the company is unlikely to be a manipulator.
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