Foryou Beneish M-Score Historical Data
The historical data trend for Foryou'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.
Foryou Beneish M-Score Chart
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Foryou Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-4.19 |
-2.29 |
-2.43 |
-2.33 |
-2.14 |
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Foryou 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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-2.32 |
-2.42 |
-2.41 |
-2.14 |
-2.13 |
Competitive Comparison of Foryou's Beneish M-Score
For the Auto Parts subindustry, Foryou'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.
Foryou's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Foryou's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Foryou's Beneish M-Score falls into.
Foryou 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 Foryou 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 * 1.0858 | + | 0.528 * 1.0006 | + | 0.404 * 0.7756 | + | 0.892 * 1.3578 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8745 | + | 4.679 * -0.000393 | - | 0.327 * 0.9345 |
| = | -2.13 |
* 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 ¥3,825 Mil.
Revenue was 1990.785 + 2339.947 + 1929.207 + 1552.279 = ¥7,812 Mil.
Gross Profit was 429.308 + 536.402 + 422.111 + 343.721 = ¥1,732 Mil.
Total Current Assets was ¥6,921 Mil.
Total Assets was ¥9,806 Mil.
Property, Plant and Equipment(Net PPE) was ¥2,047 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥313 Mil.
Total Current Liabilities was ¥3,374 Mil.
Long-Term Debt & Capital Lease Obligation was ¥2 Mil.
Net Income was 142.284 + 167.324 + 115.774 + 104.189 = ¥530 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0 Mil.
Cash Flow from Operations was 105.267 + 279.067 + -110.886 + 259.98 = ¥533 Mil.
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Total Receivables was ¥2,595 Mil.
Revenue was 1315.429 + 1629.489 + 1523.131 + 1285.418 = ¥5,753 Mil.
Gross Profit was 293.634 + 366.037 + 345.457 + 270.809 = ¥1,276 Mil.
Total Current Assets was ¥4,641 Mil.
Total Assets was ¥7,088 Mil.
Property, Plant and Equipment(Net PPE) was ¥1,666 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥264 Mil.
Total Current Liabilities was ¥2,550 Mil.
Long-Term Debt & Capital Lease Obligation was ¥61 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) |
| = | (3825.376 / 7812.218) | / | (2594.661 / 5753.467) |
| = | 0.489666 | / | 0.450973 |
| | = | 1.0858 |
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) |
| = | (1275.937 / 5753.467) | / | (1731.542 / 7812.218) |
| = | 0.221768 | / | 0.221645 |
| | = | 1.0006 |
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 - (6921.252 + 2046.812) / 9805.985) | / | (1 - (4641.301 + 1665.799) / 7087.991) |
| = | 0.08545 | / | 0.110171 |
| | = | 0.7756 |
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 |
| = | 7812.218 | / | 5753.467 |
| | = | 1.3578 |
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 + 1665.799)) | / | (0 / (0 + 2046.812)) |
| = | 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) |
| = | (313.253 / 7812.218) | / | (263.798 / 5753.467) |
| = | 0.040098 | / | 0.04585 |
| | = | 0.8745 |
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) |
| = | ((2.149 + 3373.501) / 9805.985) | / | ((61.191 + 2549.782) / 7087.991) |
| = | 0.344244 | / | 0.368366 |
| | = | 0.9345 |
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 |
| = | (529.571 - 0 | - | 533.428) | / | 9805.985 |
| | = | -0.000393 |
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.
Foryou has a M-score of -2.13 suggests that the company is unlikely to be a manipulator.
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