Appotronics Beneish M-Score Historical Data
The historical data trend for Appotronics'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.
Appotronics Beneish M-Score Chart
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Appotronics Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.37 |
-1.43 |
-2.44 |
-3.06 |
-2.79 |
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Appotronics Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
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Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-3.04 |
-3.21 |
-3.04 |
-2.79 |
-2.35 |
Competitive Comparison of Appotronics's Beneish M-Score
For the Consumer Electronics subindustry, Appotronics'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.
Appotronics's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Appotronics's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Appotronics's Beneish M-Score falls into.
Appotronics 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 Appotronics 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 * 1.5474 | + | 0.528 * 0.931 | + | 0.404 * 1.0506 | + | 0.892 * 0.8886 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.897 | + | 4.679 * -0.06684 | - | 0.327 * 0.8811 |
| = | -2.35 |
* 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 ¥247 Mil.
Revenue was 445.039 + 562.728 + 577.38 + 614.236 = ¥2,199 Mil.
Gross Profit was 144.355 + 172.336 + 224.673 + 242.25 = ¥784 Mil.
Total Current Assets was ¥2,885 Mil.
Total Assets was ¥4,168 Mil.
Property, Plant and Equipment(Net PPE) was ¥703 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥341 Mil.
Total Current Liabilities was ¥883 Mil.
Long-Term Debt & Capital Lease Obligation was ¥417 Mil.
Net Income was 44.543 + -25.372 + 53.645 + 61.26 = ¥134 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0 Mil.
Cash Flow from Operations was 12.225 + 155.149 + 94.194 + 151.07 = ¥413 Mil.
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Total Receivables was ¥180 Mil.
Revenue was 459.013 + 665.338 + 606.484 + 744.182 = ¥2,475 Mil.
Gross Profit was 162.34 + 240.358 + 204.293 + 213.974 = ¥821 Mil.
Total Current Assets was ¥3,022 Mil.
Total Assets was ¥4,358 Mil.
Property, Plant and Equipment(Net PPE) was ¥758 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥428 Mil.
Total Current Liabilities was ¥881 Mil.
Long-Term Debt & Capital Lease Obligation was ¥661 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) |
| = | (247.34 / 2199.383) | / | (179.872 / 2475.017) |
| = | 0.112459 | / | 0.072675 |
| | = | 1.5474 |
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) |
| = | (820.965 / 2475.017) | / | (783.614 / 2199.383) |
| = | 0.331701 | / | 0.356288 |
| | = | 0.931 |
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 - (2885.022 + 702.673) / 4167.617) | / | (1 - (3022.039 + 758.499) / 4357.74) |
| = | 0.13915 | / | 0.132454 |
| | = | 1.0506 |
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 |
| = | 2199.383 | / | 2475.017 |
| | = | 0.8886 |
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 + 758.499)) | / | (0 / (0 + 702.673)) |
| = | 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) |
| = | (341.083 / 2199.383) | / | (427.91 / 2475.017) |
| = | 0.155081 | / | 0.172892 |
| | = | 0.897 |
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) |
| = | ((416.523 + 882.857) / 4167.617) | / | ((660.565 + 881.379) / 4357.74) |
| = | 0.31178 | / | 0.35384 |
| | = | 0.8811 |
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 |
| = | (134.076 - 0 | - | 412.638) | / | 4167.617 |
| | = | -0.06684 |
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.
Appotronics has a M-score of -2.35 suggests that the company is unlikely to be a manipulator.
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