Terumo Beneish M-Score Historical Data
The historical data trend for Terumo'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.
Terumo Beneish M-Score Chart
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Terumo Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.61 |
-2.23 |
-2.52 |
-2.46 |
-2.41 |
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Terumo Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.44 |
-2.41 |
-2.45 |
-2.68 |
-2.61 |
Competitive Comparison of Terumo's Beneish M-Score
For the Medical Instruments & Supplies subindustry, Terumo'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.
Terumo's Beneish M-Score Distribution in the Medical Devices & Instruments Industry
For the Medical Devices & Instruments industry and Healthcare sector, Terumo's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Terumo's Beneish M-Score falls into.
Terumo 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 Terumo 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 * 0.9113 | + | 0.528 * 0.9475 | + | 0.404 * 1.012 | + | 0.892 * 1.0726 | + | 0.115 * 0.9697 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0033 | + | 4.679 * -0.041406 | - | 0.327 * 0.8956 |
| = | -2.68 |
* 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 $1,210 Mil.
Revenue was 1713.43 + 1752.249 + 1635.588 + 1594.675 = $6,696 Mil.
Gross Profit was 943.456 + 975.503 + 871.462 + 829.897 = $3,620 Mil.
Total Current Assets was $4,785 Mil.
Total Assets was $12,207 Mil.
Property, Plant and Equipment(Net PPE) was $2,799 Mil.
Depreciation, Depletion and Amortization(DDA) was $560 Mil.
Selling, General, & Admin. Expense(SGA) was $2,483 Mil.
Total Current Liabilities was $1,715 Mil.
Long-Term Debt & Capital Lease Obligation was $1,039 Mil.
Net Income was 230.265 + 205.052 + 214.69 + 176.727 = $827 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 281.976 + 456.084 + 226.143 + 367.978 = $1,332 Mil.
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Total Receivables was $1,237 Mil.
Revenue was 1660.47 + 1546.356 + 1522.743 + 1512.865 = $6,242 Mil.
Gross Profit was 879.175 + 801.211 + 776.744 + 740.826 = $3,198 Mil.
Total Current Assets was $4,647 Mil.
Total Assets was $11,749 Mil.
Property, Plant and Equipment(Net PPE) was $2,705 Mil.
Depreciation, Depletion and Amortization(DDA) was $522 Mil.
Selling, General, & Admin. Expense(SGA) was $2,307 Mil.
Total Current Liabilities was $2,439 Mil.
Long-Term Debt & Capital Lease Obligation was $521 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) |
| = | (1209.53 / 6695.942) | / | (1237.353 / 6242.434) |
| = | 0.180636 | / | 0.198216 |
| | = | 0.9113 |
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) |
| = | (3197.956 / 6242.434) | / | (3620.318 / 6695.942) |
| = | 0.512293 | / | 0.540673 |
| | = | 0.9475 |
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 - (4784.789 + 2799.018) / 12207.103) | / | (1 - (4646.514 + 2705.459) / 11749.197) |
| = | 0.378738 | / | 0.374257 |
| | = | 1.012 |
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 |
| = | 6695.942 | / | 6242.434 |
| | = | 1.0726 |
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)) |
| = | (521.96 / (521.96 + 2705.459)) | / | (560.284 / (560.284 + 2799.018)) |
| = | 0.161727 | / | 0.166786 |
| | = | 0.9697 |
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) |
| = | (2483.012 / 6695.942) | / | (2307.297 / 6242.434) |
| = | 0.370823 | / | 0.369615 |
| | = | 1.0033 |
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) |
| = | ((1039.052 + 1715.361) / 12207.103) | / | ((520.734 + 2439.494) / 11749.197) |
| = | 0.22564 | / | 0.251952 |
| | = | 0.8956 |
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 |
| = | (826.734 - 0 | - | 1332.181) | / | 12207.103 |
| | = | -0.041406 |
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.
Terumo has a M-score of -2.68 suggests that the company is unlikely to be a manipulator.
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