Infodema Beneish M-Score Historical Data
The historical data trend for Infodema'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.
Infodema Beneish M-Score Chart
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Infodema Annual Data
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Trend |
Dec10 |
Dec11 |
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Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
| Beneish M-Score |
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-3.51 |
0.61 |
-2.53 |
-2.97 |
-1.25 |
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Infodema Quarterly Data
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Sep15 |
Dec15 |
Mar16 |
Jun16 |
Sep16 |
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Mar17 |
Jun17 |
Sep17 |
Dec17 |
Mar18 |
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
| Beneish M-Score |
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-2.37 |
-2.15 |
-1.25 |
-1.22 |
-2.06 |
Infodema Beneish M-Score Competitor Comparison
For the Lumber & Wood Production subindustry, Infodema'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.
Infodema Beneish M-Score vs Forest Products Industry
For the Forest Products industry and Basic Materials sector, Infodema's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Infodema's Beneish M-Score falls into.
Infodema 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 Infodema 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 * 0.3628 | + | 0.528 * -1.4609 | + | 0.404 * 1.1951 | + | 0.892 * 1.6573 | + | 0.115 * 1.7205 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6238 | + | 4.679 * 0.323379 | - | 0.327 * 1.1583 |
| = | -2.09 |
* 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 (Jun20) TTM: | Last Year (Jun19) TTM: |
Total Receivables was CLP1,339 Mil.
Revenue was 2212.034 + 2405.093 + 10599.448 + 2539.477 = CLP17,756 Mil.
Gross Profit was -203.036 + -84.022 + 2819.792 + -406.312 = CLP2,126 Mil.
Total Current Assets was CLP2,521 Mil.
Total Assets was CLP20,912 Mil.
Property, Plant and Equipment(Net PPE) was CLP13,743 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP16 Mil.
Selling, General, & Admin. Expense(SGA) was CLP267 Mil.
Total Current Liabilities was CLP6,849 Mil.
Long-Term Debt & Capital Lease Obligation was CLP7,205 Mil.
Net Income was -1336.537 + -149.954 + 1463.336 + -949.362 = CLP-973 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = CLP0 Mil.
Cash Flow from Operations was -2108.398 + -1737.894 + -2074.833 + -1813.948 = CLP-7,735 Mil.
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Total Receivables was CLP2,226 Mil.
Revenue was 3689.087 + 4327.743 + -2851.269 + 5548.047 = CLP10,714 Mil.
Gross Profit was -30.577 + 280.173 + -2949.054 + 825.031 = CLP-1,874 Mil.
Total Current Assets was CLP5,336 Mil.
Total Assets was CLP24,446 Mil.
Property, Plant and Equipment(Net PPE) was CLP14,564 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP30 Mil.
Selling, General, & Admin. Expense(SGA) was CLP258 Mil.
Total Current Liabilities was CLP8,476 Mil.
Long-Term Debt & Capital Lease Obligation was CLP5,708 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) |
| = | (1338.586 / 17756.052) | / | (2226.191 / 10713.608) |
| = | 0.075388 | / | 0.207791 |
| | = | 0.3628 |
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) |
| = | (-1874.427 / 10713.608) | / | (2126.422 / 17756.052) |
| = | -0.174958 | / | 0.119758 |
| | = | -1.4609 |
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 - (2521.305 + 13743.229) / 20912.182) | / | (1 - (5336.082 + 14563.885) / 24446.233) |
| = | 0.222246 | / | 0.18597 |
| | = | 1.1951 |
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 |
| = | 17756.052 | / | 10713.608 |
| | = | 1.6573 |
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)) |
| = | (29.55 / (29.55 + 14563.885)) | / | (16.197 / (16.197 + 13743.229)) |
| = | 0.002025 | / | 0.001177 |
| | = | 1.7205 |
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) |
| = | (267.174 / 17756.052) | / | (258.432 / 10713.608) |
| = | 0.015047 | / | 0.024122 |
| | = | 0.6238 |
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) |
| = | ((7205.189 + 6849.436) / 20912.182) | / | ((5708.45 + 8475.549) / 24446.233) |
| = | 0.672078 | / | 0.580212 |
| | = | 1.1583 |
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 |
| = | (-972.517 - 0 | - | -7735.073) | / | 20912.182 |
| | = | 0.323379 |
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.
Infodema has a M-score of -2.09 suggests that the company is unlikely to be a manipulator.
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