ITOCHU Beneish M-Score Historical Data
The historical data trend for ITOCHU'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.
ITOCHU Beneish M-Score Chart
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ITOCHU Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.95 |
-2.72 |
-2.20 |
-2.44 |
-2.45 |
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ITOCHU 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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-2.44 |
-2.46 |
-2.46 |
-2.50 |
-2.45 |
Competitive Comparison of ITOCHU's Beneish M-Score
For the Conglomerates subindustry, ITOCHU'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.
ITOCHU's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, ITOCHU's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where ITOCHU's Beneish M-Score falls into.
ITOCHU 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 ITOCHU 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 * 1.0822 | + | 0.528 * 0.9603 | + | 0.404 * 1.0202 | + | 0.892 * 0.9083 | + | 0.115 * 1.0022 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0651 | + | 4.679 * -0.012189 | - | 0.327 * 0.9983 |
| = | -2.57 |
* 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 €19,070 Mil.
Revenue was 21976.851 + 23418.113 + 21710.533 + 21864.026 = €88,970 Mil.
Gross Profit was 3586.099 + 3698.717 + 3484.23 + 3381.421 = €14,150 Mil.
Total Current Assets was €34,534 Mil.
Total Assets was €88,978 Mil.
Property, Plant and Equipment(Net PPE) was €12,961 Mil.
Depreciation, Depletion and Amortization(DDA) was €2,665 Mil.
Selling, General, & Admin. Expense(SGA) was €9,641 Mil.
Total Current Liabilities was €26,666 Mil.
Long-Term Debt & Capital Lease Obligation was €21,150 Mil.
Net Income was 1167.217 + 1266.094 + 1265.402 + 1392.334 = €5,091 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 2160.467 + 1000.365 + 1617.208 + 1397.584 = €6,176 Mil.
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Total Receivables was €19,400 Mil.
Revenue was 23767.907 + 24853.759 + 25475.816 + 23854.602 = €97,952 Mil.
Gross Profit was 3462.607 + 3848.061 + 3942.956 + 3707.701 = €14,961 Mil.
Total Current Assets was €35,786 Mil.
Total Assets was €91,620 Mil.
Property, Plant and Equipment(Net PPE) was €13,965 Mil.
Depreciation, Depletion and Amortization(DDA) was €2,879 Mil.
Selling, General, & Admin. Expense(SGA) was €9,966 Mil.
Total Current Liabilities was €27,565 Mil.
Long-Term Debt & Capital Lease Obligation was €21,754 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) |
| = | (19069.668 / 88969.523) | / | (19400.106 / 97952.084) |
| = | 0.214339 | / | 0.198057 |
| | = | 1.0822 |
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) |
| = | (14961.325 / 97952.084) | / | (14150.467 / 88969.523) |
| = | 0.152741 | / | 0.159048 |
| | = | 0.9603 |
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 - (34534.097 + 12960.785) / 88977.77) | / | (1 - (35786.352 + 13964.723) / 91619.699) |
| = | 0.466216 | / | 0.456983 |
| | = | 1.0202 |
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 |
| = | 88969.523 | / | 97952.084 |
| | = | 0.9083 |
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)) |
| = | (2879.223 / (2879.223 + 13964.723)) | / | (2665.248 / (2665.248 + 12960.785)) |
| = | 0.170935 | / | 0.170565 |
| | = | 1.0022 |
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) |
| = | (9641.444 / 88969.523) | / | (9966.448 / 97952.084) |
| = | 0.108368 | / | 0.101748 |
| | = | 1.0651 |
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) |
| = | ((21149.58 + 26665.542) / 88977.77) | / | ((21754.009 + 27565.076) / 91619.699) |
| = | 0.537383 | / | 0.538302 |
| | = | 0.9983 |
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 |
| = | (5091.047 - 0 | - | 6175.624) | / | 88977.77 |
| | = | -0.012189 |
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.
ITOCHU has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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