Seika Beneish M-Score Historical Data
The historical data trend for Seika'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.
Seika Beneish M-Score Chart
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Seika Annual Data
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Mar15 |
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Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.92 |
-2.35 |
-2.66 |
-1.81 |
-2.12 |
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Seika Quarterly Data
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Sep19 |
Dec19 |
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Mar24 |
Sep24 |
| Beneish M-Score |
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-2.12 |
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Competitive Comparison of Seika's Beneish M-Score
For the Industrial Distribution subindustry, Seika'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.
Seika's Beneish M-Score Distribution in the Industrial Distribution Industry
For the Industrial Distribution industry and Industrials sector, Seika's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Seika's Beneish M-Score falls into.
Seika 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 Seika 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 * 1.6056 | + | 0.528 * 0.8185 | + | 0.404 * 0.8832 | + | 0.892 * 0.9301 | + | 0.115 * 0.8915 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * 0.016433 | - | 0.327 * 1.1691 |
| = | -2.12 |
* 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 円53,475 Mil.
Revenue was 円86,785 Mil.
Gross Profit was 円22,658 Mil.
Total Current Assets was 円95,599 Mil.
Total Assets was 円118,543 Mil.
Property, Plant and Equipment(Net PPE) was 円4,658 Mil.
Depreciation, Depletion and Amortization(DDA) was 円681 Mil.
Selling, General, & Admin. Expense(SGA) was 円0 Mil.
Total Current Liabilities was 円70,146 Mil.
Long-Term Debt & Capital Lease Obligation was 円151 Mil.
Net Income was 円4,489 Mil.
Gross Profit was 円0 Mil.
Cash Flow from Operations was 円2,541 Mil.
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Total Receivables was 円35,809 Mil.
Revenue was 円93,311 Mil.
Gross Profit was 円19,941 Mil.
Total Current Assets was 円61,429 Mil.
Total Assets was 円79,990 Mil.
Property, Plant and Equipment(Net PPE) was 円4,591 Mil.
Depreciation, Depletion and Amortization(DDA) was 円589 Mil.
Selling, General, & Admin. Expense(SGA) was 円0 Mil.
Total Current Liabilities was 円40,473 Mil.
Long-Term Debt & Capital Lease Obligation was 円99 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) |
| = | (53475 / 86785) | / | (35809 / 93311) |
| = | 0.616178 | / | 0.38376 |
| | = | 1.6056 |
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) |
| = | (19941 / 93311) | / | (22658 / 86785) |
| = | 0.213705 | / | 0.261082 |
| | = | 0.8185 |
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 - (95599 + 4658) / 118543) | / | (1 - (61429 + 4591) / 79990) |
| = | 0.154256 | / | 0.174647 |
| | = | 0.8832 |
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 |
| = | 86785 | / | 93311 |
| | = | 0.9301 |
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)) |
| = | (589 / (589 + 4591)) | / | (681 / (681 + 4658)) |
| = | 0.113707 | / | 0.127552 |
| | = | 0.8915 |
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) |
| = | (0 / 86785) | / | (0 / 93311) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((151 + 70146) / 118543) | / | ((99 + 40473) / 79990) |
| = | 0.593008 | / | 0.507213 |
| | = | 1.1691 |
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 |
| = | (4489 - 0 | - | 2541) | / | 118543 |
| | = | 0.016433 |
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.
Seika has a M-score of -2.12 suggests that the company is unlikely to be a manipulator.
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