Schwager Beneish M-Score Historical Data
The historical data trend for Schwager'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.
Schwager Beneish M-Score Chart
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Schwager Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.19 |
-2.33 |
-1.59 |
-2.52 |
-2.71 |
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Schwager 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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-2.52 |
-2.67 |
-2.79 |
-2.81 |
-2.71 |
Competitive Comparison of Schwager's Beneish M-Score
For the Engineering & Construction subindustry, Schwager'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.
Schwager's Beneish M-Score Distribution in the Construction Industry
For the Construction industry and Industrials sector, Schwager's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Schwager's Beneish M-Score falls into.
Schwager 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 Schwager 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 * 1.115 | + | 0.528 * 0.8435 | + | 0.404 * 0.9 | + | 0.892 * 1.1626 | + | 0.115 * 0.8936 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.045 | + | 4.679 * -0.077068 | - | 0.327 * 0.9426 |
| = | -2.71 |
* 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 CLP15,592 Mil.
Revenue was 22710.103 + 20271.163 + 19140.959 + 19158.257 = CLP81,280 Mil.
Gross Profit was 4175.764 + 2895.695 + 3437.264 + 3095.194 = CLP13,604 Mil.
Total Current Assets was CLP28,132 Mil.
Total Assets was CLP57,945 Mil.
Property, Plant and Equipment(Net PPE) was CLP12,023 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP292 Mil.
Selling, General, & Admin. Expense(SGA) was CLP6,303 Mil.
Total Current Liabilities was CLP18,036 Mil.
Long-Term Debt & Capital Lease Obligation was CLP5,375 Mil.
Net Income was 789.632 + 364.885 + 485.203 + 429.871 = CLP2,070 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = CLP0 Mil.
Cash Flow from Operations was 1218.182 + 639.879 + 3224.744 + 1452.458 = CLP6,535 Mil.
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Total Receivables was CLP12,028 Mil.
Revenue was 20765.653 + 18126.03 + 15776.193 + 15243.8 = CLP69,912 Mil.
Gross Profit was 2827.399 + 1965.962 + 2675.679 + 2400.96 = CLP9,870 Mil.
Total Current Assets was CLP20,952 Mil.
Total Assets was CLP50,010 Mil.
Property, Plant and Equipment(Net PPE) was CLP11,999 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP260 Mil.
Selling, General, & Admin. Expense(SGA) was CLP5,188 Mil.
Total Current Liabilities was CLP16,994 Mil.
Long-Term Debt & Capital Lease Obligation was CLP4,443 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) |
| = | (15591.782 / 81280.482) | / | (12027.792 / 69911.676) |
| = | 0.191827 | / | 0.172043 |
| | = | 1.115 |
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) |
| = | (9870 / 69911.676) | / | (13603.917 / 81280.482) |
| = | 0.141178 | / | 0.16737 |
| | = | 0.8435 |
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 - (28131.651 + 12023.267) / 57944.544) | / | (1 - (20952.405 + 11998.773) / 50010.443) |
| = | 0.307011 | / | 0.341114 |
| | = | 0.9 |
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 |
| = | 81280.482 | / | 69911.676 |
| | = | 1.1626 |
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)) |
| = | (259.862 / (259.862 + 11998.773)) | / | (292.138 / (292.138 + 12023.267)) |
| = | 0.021198 | / | 0.023721 |
| | = | 0.8936 |
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) |
| = | (6303.003 / 81280.482) | / | (5187.733 / 69911.676) |
| = | 0.077546 | / | 0.074204 |
| | = | 1.045 |
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) |
| = | ((5374.644 + 18036.261) / 57944.544) | / | ((4442.84 + 16993.76) / 50010.443) |
| = | 0.404023 | / | 0.428642 |
| | = | 0.9426 |
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 |
| = | (2069.591 - 0 | - | 6535.263) | / | 57944.544 |
| | = | -0.077068 |
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.
Schwager has a M-score of -2.71 suggests that the company is unlikely to be a manipulator.
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