Fadu Beneish M-Score Historical Data
The historical data trend for Fadu'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.
Fadu Beneish M-Score Chart
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Fadu Annual Data
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Trend |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
|
- |
- |
- |
-3.74 |
1.49 |
|
Fadu Quarterly Data
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|
Dec20 |
Dec21 |
Mar22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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|
|
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-3.74 |
-4.99 |
- |
11.93 |
1.49 |
Competitive Comparison of Fadu's Beneish M-Score
For the Semiconductors subindustry, Fadu'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.
Fadu's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Fadu's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Fadu's Beneish M-Score falls into.
Fadu 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 Fadu 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 * 1.9775 | + | 0.528 * 3.7234 | + | 0.404 * 1.7349 | + | 0.892 * 1.936 | + | 0.115 * 0.7436 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3726 | + | 4.679 * 0.135957 | - | 0.327 * 1.1392 |
| = | 1.49 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩15,409 Mil.
Revenue was 23983.5 + 10094.871 + 7092.516 + 2331.859 = ₩43,503 Mil.
Gross Profit was 2499.468 + 2242.097 + 555.652 + 471.98 = ₩5,769 Mil.
Total Current Assets was ₩98,648 Mil.
Total Assets was ₩134,427 Mil.
Property, Plant and Equipment(Net PPE) was ₩28,209 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩11,459 Mil.
Selling, General, & Admin. Expense(SGA) was ₩16,157 Mil.
Total Current Liabilities was ₩31,263 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,499 Mil.
Net Income was -23744.364 + -30592.789 + -21054.538 + -15172.276 = ₩-90,564 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -526.05 + -36067.092 + -38936.555 + -33310.625 = ₩-108,840 Mil.
|
Total Receivables was ₩4,025 Mil.
Revenue was 4426.84 + 320.81 + 59.408 + 17663.847 = ₩22,471 Mil.
Gross Profit was -2205.47 + -112.064 + -119.286 + 13532.612 = ₩11,096 Mil.
Total Current Assets was ₩203,276 Mil.
Total Assets was ₩243,662 Mil.
Property, Plant and Equipment(Net PPE) was ₩32,476 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩8,885 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,080 Mil.
Total Current Liabilities was ₩50,212 Mil.
Long-Term Debt & Capital Lease Obligation was ₩6,687 Mil.
|
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) |
| = | (15408.687 / 43502.746) | / | (4024.942 / 22470.905) |
| = | 0.3542 | / | 0.179118 |
| | = | 1.9775 |
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) |
| = | (11095.792 / 22470.905) | / | (5769.197 / 43502.746) |
| = | 0.493785 | / | 0.132617 |
| | = | 3.7234 |
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 - (98647.617 + 28208.96) / 134427.343) | / | (1 - (203276.136 + 32475.761) / 243661.794) |
| = | 0.056319 | / | 0.032463 |
| | = | 1.7349 |
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 |
| = | 43502.746 | / | 22470.905 |
| | = | 1.936 |
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)) |
| = | (8884.847 / (8884.847 + 32475.761)) | / | (11459.189 / (11459.189 + 28208.96)) |
| = | 0.214814 | / | 0.288876 |
| | = | 0.7436 |
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) |
| = | (16156.961 / 43502.746) | / | (6080.367 / 22470.905) |
| = | 0.371401 | / | 0.270588 |
| | = | 1.3726 |
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) |
| = | ((4499.156 + 31263.025) / 134427.343) | / | ((6686.918 + 50212.158) / 243661.794) |
| = | 0.266034 | / | 0.233517 |
| | = | 1.1392 |
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 |
| = | (-90563.967 - 0 | - | -108840.322) | / | 134427.343 |
| | = | 0.135957 |
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.
Fadu has a M-score of 1.49 signals that the company is likely to be a manipulator.
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