Aloys Beneish M-Score Historical Data
The historical data trend for Aloys'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.
Aloys Beneish M-Score Chart
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Aloys Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
-2.96 |
-0.09 |
-1.89 |
-1.57 |
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Aloys Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.86 |
-2.53 |
-2.23 |
-1.57 |
-0.92 |
Competitive Comparison of Aloys's Beneish M-Score
For the Shell Companies subindustry, Aloys'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.
Aloys's Beneish M-Score Distribution in the Diversified Financial Services Industry
For the Diversified Financial Services industry and Financial Services sector, Aloys's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Aloys's Beneish M-Score falls into.
Aloys 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 Aloys 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 * 2.0506 | + | 0.528 * 0.7895 | + | 0.404 * 4.2218 | + | 0.892 * 0.9811 | + | 0.115 * 1.2221 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3521 | + | 4.679 * -0.098784 | - | 0.327 * 1.2591 |
| = | -0.92 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩17,560 Mil.
Revenue was 6579.7 + 7330.079 + 5834.44 + 7418.869 = ₩27,163 Mil.
Gross Profit was 2687.56 + 3135.62 + 2329.54 + 2965.816 = ₩11,119 Mil.
Total Current Assets was ₩42,801 Mil.
Total Assets was ₩61,956 Mil.
Property, Plant and Equipment(Net PPE) was ₩760 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩464 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,375 Mil.
Total Current Liabilities was ₩18,677 Mil.
Long-Term Debt & Capital Lease Obligation was ₩230 Mil.
Net Income was 1026.385 + 1885.444 + 1099.823 + 725.109 = ₩4,737 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3401.841 + 3962.182 + 2041.484 + 1451.534 = ₩10,857 Mil.
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Total Receivables was ₩8,728 Mil.
Revenue was 6000.138 + 10114.07 + 5189.072 + 6383.651 = ₩27,687 Mil.
Gross Profit was 2013.369 + 3471.491 + 1661.879 + 1800.654 = ₩8,947 Mil.
Total Current Assets was ₩39,536 Mil.
Total Assets was ₩43,099 Mil.
Property, Plant and Equipment(Net PPE) was ₩532 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩459 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,037 Mil.
Total Current Liabilities was ₩10,215 Mil.
Long-Term Debt & Capital Lease Obligation was ₩230 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) |
| = | (17560.162 / 27163.088) | / | (8728.449 / 27686.931) |
| = | 0.646471 | / | 0.315255 |
| | = | 2.0506 |
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) |
| = | (8947.393 / 27686.931) | / | (11118.536 / 27163.088) |
| = | 0.323163 | / | 0.409325 |
| | = | 0.7895 |
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 - (42800.509 + 760.22) / 61956.129) | / | (1 - (39535.721 + 532.235) / 43099.04) |
| = | 0.29691 | / | 0.070328 |
| | = | 4.2218 |
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 |
| = | 27163.088 | / | 27686.931 |
| | = | 0.9811 |
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)) |
| = | (459.072 / (459.072 + 532.235)) | / | (463.831 / (463.831 + 760.22)) |
| = | 0.463098 | / | 0.378931 |
| | = | 1.2221 |
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) |
| = | (1375.074 / 27163.088) | / | (1036.597 / 27686.931) |
| = | 0.050623 | / | 0.03744 |
| | = | 1.3521 |
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) |
| = | ((229.697 + 18676.84) / 61956.129) | / | ((230 + 10215.448) / 43099.04) |
| = | 0.30516 | / | 0.242359 |
| | = | 1.2591 |
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 |
| = | (4736.761 - 0 | - | 10857.041) | / | 61956.129 |
| | = | -0.098784 |
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.
Aloys has a M-score of -0.92 signals that the company is likely to be a manipulator.
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