ASJ Beneish M-Score Historical Data
The historical data trend for ASJ'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.
ASJ Beneish M-Score Chart
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ASJ Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.51 |
-3.06 |
-3.41 |
-2.92 |
-2.50 |
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ASJ Quarterly Data
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Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Sep24 |
| Beneish M-Score |
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-3.15 |
-2.81 |
-2.65 |
-2.50 |
-1.99 |
Competitive Comparison of ASJ's Beneish M-Score
For the Software - Infrastructure subindustry, ASJ'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.
ASJ's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, ASJ's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where ASJ's Beneish M-Score falls into.
ASJ 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 ASJ 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 * 1.4932 | + | 0.528 * 0.9242 | + | 0.404 * 1.0564 | + | 0.892 * 0.8338 | + | 0.115 * 1.3759 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9311 | + | 4.679 * 0.029207 | - | 0.327 * 0.9624 |
| = | -1.99 |
* 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 (Jun23) TTM: |
Total Receivables was 円497 Mil.
Revenue was 0 + 845.02 + 673.396 + 733.5 = 円2,252 Mil.
Gross Profit was 0 + 370.555 + 262.842 + 273.374 = 円907 Mil.
Total Current Assets was 円1,685 Mil.
Total Assets was 円4,098 Mil.
Property, Plant and Equipment(Net PPE) was 円1,512 Mil.
Depreciation, Depletion and Amortization(DDA) was 円199 Mil.
Selling, General, & Admin. Expense(SGA) was 円755 Mil.
Total Current Liabilities was 円1,150 Mil.
Long-Term Debt & Capital Lease Obligation was 円44 Mil.
Net Income was 0 + 135.38 + 8.324 + 13.64 = 円157 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 0 + 30.879 + 81.1 + -74.316 = 円38 Mil.
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Total Receivables was 円400 Mil.
Revenue was 595.048 + 735.319 + 669.703 + 700.783 = 円2,701 Mil.
Gross Profit was 202.589 + 282.398 + 264.152 + 255.923 = 円1,005 Mil.
Total Current Assets was 円1,651 Mil.
Total Assets was 円3,988 Mil.
Property, Plant and Equipment(Net PPE) was 円1,507 Mil.
Depreciation, Depletion and Amortization(DDA) was 円288 Mil.
Selling, General, & Admin. Expense(SGA) was 円972 Mil.
Total Current Liabilities was 円1,147 Mil.
Long-Term Debt & Capital Lease Obligation was 円60 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) |
| = | (497.389 / 2251.916) | / | (399.517 / 2700.853) |
| = | 0.220874 | / | 0.147923 |
| | = | 1.4932 |
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) |
| = | (1005.062 / 2700.853) | / | (906.771 / 2251.916) |
| = | 0.372128 | / | 0.402666 |
| | = | 0.9242 |
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 - (1684.888 + 1512.096) / 4097.714) | / | (1 - (1651.124 + 1506.692) / 3987.565) |
| = | 0.219813 | / | 0.208084 |
| | = | 1.0564 |
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 |
| = | 2251.916 | / | 2700.853 |
| | = | 0.8338 |
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)) |
| = | (287.667 / (287.667 + 1506.692)) | / | (199.42 / (199.42 + 1512.096)) |
| = | 0.160317 | / | 0.116517 |
| | = | 1.3759 |
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) |
| = | (754.682 / 2251.916) | / | (972.141 / 2700.853) |
| = | 0.335129 | / | 0.359939 |
| | = | 0.9311 |
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) |
| = | ((43.947 + 1149.644) / 4097.714) | / | ((60.207 + 1146.651) / 3987.565) |
| = | 0.291282 | / | 0.302655 |
| | = | 0.9624 |
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 |
| = | (157.344 - 0 | - | 37.663) | / | 4097.714 |
| | = | 0.029207 |
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.
ASJ has a M-score of -1.99 suggests that the company is unlikely to be a manipulator.
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