Yasuda Logistics Beneish M-Score Historical Data
The historical data trend for Yasuda Logistics'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.
Yasuda Logistics Beneish M-Score Chart
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Yasuda Logistics Annual Data
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Mar14 |
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Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.57 |
-2.79 |
-2.39 |
-2.45 |
-2.40 |
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Yasuda Logistics Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
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Dec20 |
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Dec23 |
| Beneish M-Score |
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-2.33 |
-2.40 |
-2.35 |
-2.45 |
-2.47 |
Competitive Comparison of Yasuda Logistics's Beneish M-Score
For the Specialty Business Services subindustry, Yasuda Logistics'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.
Yasuda Logistics's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, Yasuda Logistics's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Yasuda Logistics's Beneish M-Score falls into.
Yasuda Logistics 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 Yasuda Logistics 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 * 1.0883 | + | 0.528 * 0.9676 | + | 0.404 * 1.1318 | + | 0.892 * 1.0776 | + | 0.115 * 0.984 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1197 | + | 4.679 * -0.026945 | - | 0.327 * 1.0867 |
| = | -2.47 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was 円12,283 Mil.
Revenue was 17364 + 16531 + 16363 + 14391 = 円64,649 Mil.
Gross Profit was 2229 + 1920 + 1853 + 1520 = 円7,522 Mil.
Total Current Assets was 円40,761 Mil.
Total Assets was 円200,928 Mil.
Property, Plant and Equipment(Net PPE) was 円86,775 Mil.
Depreciation, Depletion and Amortization(DDA) was 円3,980 Mil.
Selling, General, & Admin. Expense(SGA) was 円549 Mil.
Total Current Liabilities was 円20,019 Mil.
Long-Term Debt & Capital Lease Obligation was 円66,696 Mil.
Net Income was 529 + 711 + 464 + 411 = 円2,115 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 1665 + 1725 + 1340 + 2799 = 円7,529 Mil.
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Total Receivables was 円10,473 Mil.
Revenue was 15775 + 15206 + 14381 + 14630 = 円59,992 Mil.
Gross Profit was 1962 + 1697 + 1492 + 1603 = 円6,754 Mil.
Total Current Assets was 円27,377 Mil.
Total Assets was 円158,053 Mil.
Property, Plant and Equipment(Net PPE) was 円79,669 Mil.
Depreciation, Depletion and Amortization(DDA) was 円3,593 Mil.
Selling, General, & Admin. Expense(SGA) was 円455 Mil.
Total Current Liabilities was 円15,552 Mil.
Long-Term Debt & Capital Lease Obligation was 円47,219 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) |
| = | (12283 / 64649) | / | (10473 / 59992) |
| = | 0.189995 | / | 0.174573 |
| | = | 1.0883 |
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) |
| = | (6754 / 59992) | / | (7522 / 64649) |
| = | 0.112582 | / | 0.116351 |
| | = | 0.9676 |
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 - (40761 + 86775) / 200928) | / | (1 - (27377 + 79669) / 158053) |
| = | 0.365265 | / | 0.322721 |
| | = | 1.1318 |
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 |
| = | 64649 | / | 59992 |
| | = | 1.0776 |
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)) |
| = | (3593 / (3593 + 79669)) | / | (3980 / (3980 + 86775)) |
| = | 0.043153 | / | 0.043854 |
| | = | 0.984 |
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) |
| = | (549 / 64649) | / | (455 / 59992) |
| = | 0.008492 | / | 0.007584 |
| | = | 1.1197 |
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) |
| = | ((66696 + 20019) / 200928) | / | ((47219 + 15552) / 158053) |
| = | 0.431573 | / | 0.397152 |
| | = | 1.0867 |
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 |
| = | (2115 - 0 | - | 7529) | / | 200928 |
| | = | -0.026945 |
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.
Yasuda Logistics has a M-score of -2.47 suggests that the company is unlikely to be a manipulator.
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