Aerosun Beneish M-Score Historical Data
The historical data trend for Aerosun'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.
Aerosun Beneish M-Score Chart
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Aerosun Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.58 |
-2.83 |
-2.67 |
-2.32 |
-2.54 |
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Aerosun 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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-2.69 |
-2.09 |
-2.26 |
-2.54 |
-2.49 |
Competitive Comparison of Aerosun's Beneish M-Score
For the Auto Parts subindustry, Aerosun'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.
Aerosun's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Aerosun's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Aerosun's Beneish M-Score falls into.
Aerosun 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 Aerosun 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 * 1.3577 | + | 0.528 * 1.0641 | + | 0.404 * 1.0149 | + | 0.892 * 0.8822 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9742 | + | 4.679 * -0.063397 | - | 0.327 * 0.9386 |
| = | -2.49 |
* 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 ¥1,871 Mil.
Revenue was 358.903 + 1412.975 + 756.069 + 1132.973 = ¥3,661 Mil.
Gross Profit was 14.767 + 262.197 + 126.497 + 147.097 = ¥551 Mil.
Total Current Assets was ¥3,576 Mil.
Total Assets was ¥5,321 Mil.
Property, Plant and Equipment(Net PPE) was ¥1,118 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥159 Mil.
Total Current Liabilities was ¥2,854 Mil.
Long-Term Debt & Capital Lease Obligation was ¥1 Mil.
Net Income was -76.818 + 53.374 + 4.963 + 25.756 = ¥7 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0 Mil.
Cash Flow from Operations was -486.687 + 1128.728 + -21.771 + -275.632 = ¥345 Mil.
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Total Receivables was ¥1,562 Mil.
Revenue was 515.672 + 1585.249 + 924.995 + 1123.9 = ¥4,150 Mil.
Gross Profit was 101.375 + 277.039 + 126.323 + 159.372 = ¥664 Mil.
Total Current Assets was ¥4,027 Mil.
Total Assets was ¥5,870 Mil.
Property, Plant and Equipment(Net PPE) was ¥1,161 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥185 Mil.
Total Current Liabilities was ¥3,355 Mil.
Long-Term Debt & Capital Lease Obligation was ¥0 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) |
| = | (1870.971 / 3660.92) | / | (1562.042 / 4149.816) |
| = | 0.511066 | / | 0.376412 |
| | = | 1.3577 |
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) |
| = | (664.109 / 4149.816) | / | (550.558 / 3660.92) |
| = | 0.160033 | / | 0.150388 |
| | = | 1.0641 |
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 - (3575.879 + 1117.636) / 5321.436) | / | (1 - (4026.6 + 1161.071) / 5870.191) |
| = | 0.117998 | / | 0.116269 |
| | = | 1.0149 |
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 |
| = | 3660.92 | / | 4149.816 |
| | = | 0.8822 |
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)) |
| = | (0 / (0 + 1161.071)) | / | (0 / (0 + 1117.636)) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (159.212 / 3660.92) | / | (185.255 / 4149.816) |
| = | 0.04349 | / | 0.044642 |
| | = | 0.9742 |
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) |
| = | ((0.926 + 2853.519) / 5321.436) | / | ((0 + 3354.709) / 5870.191) |
| = | 0.536405 | / | 0.571482 |
| | = | 0.9386 |
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 |
| = | (7.275 - 0 | - | 344.638) | / | 5321.436 |
| | = | -0.063397 |
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.
Aerosun has a M-score of -2.49 suggests that the company is unlikely to be a manipulator.
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