Sysmex Beneish M-Score Historical Data
The historical data trend for Sysmex'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.
Sysmex Beneish M-Score Chart
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Sysmex Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.75 |
-2.55 |
-2.47 |
-2.59 |
-2.42 |
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Sysmex 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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-2.59 |
-2.71 |
-2.63 |
-2.61 |
-2.42 |
Competitive Comparison of Sysmex's Beneish M-Score
For the Medical Instruments & Supplies subindustry, Sysmex'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.
Sysmex's Beneish M-Score Distribution in the Medical Devices & Instruments Industry
For the Medical Devices & Instruments industry and Healthcare sector, Sysmex's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sysmex's Beneish M-Score falls into.
Sysmex 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 Sysmex 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 * 1.106 | + | 0.528 * 1.0018 | + | 0.404 * 1.0206 | + | 0.892 * 1.1243 | + | 0.115 * 1.0098 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0591 | + | 4.679 * -0.023053 | - | 0.327 * 1.1172 |
| = | -2.42 |
* 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157,067 Mil.
Revenue was 134985 + 113826 + 117347 + 95351 = 円461,509 Mil.
Gross Profit was 70723 + 60759 + 60606 + 50408 = 円242,496 Mil.
Total Current Assets was 円343,459 Mil.
Total Assets was 円618,920 Mil.
Property, Plant and Equipment(Net PPE) was 円116,693 Mil.
Depreciation, Depletion and Amortization(DDA) was 円35,888 Mil.
Selling, General, & Admin. Expense(SGA) was 円133,797 Mil.
Total Current Liabilities was 円118,084 Mil.
Long-Term Debt & Capital Lease Obligation was 円46,680 Mil.
Net Income was 15175 + 12277 + 13565 + 8620 = 円49,637 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 25037 + 8197 + 19328 + 11343 = 円63,905 Mil.
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Total Receivables was 円126,319 Mil.
Revenue was 111759 + 104721 + 107992 + 86029 = 円410,501 Mil.
Gross Profit was 61216 + 56327 + 55577 + 42961 = 円216,081 Mil.
Total Current Assets was 円295,491 Mil.
Total Assets was 円531,074 Mil.
Property, Plant and Equipment(Net PPE) was 円102,106 Mil.
Depreciation, Depletion and Amortization(DDA) was 円31,807 Mil.
Selling, General, & Admin. Expense(SGA) was 円112,370 Mil.
Total Current Liabilities was 円111,102 Mil.
Long-Term Debt & Capital Lease Obligation was 円15,442 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) |
| = | (157067 / 461509) | / | (126319 / 410501) |
| = | 0.340334 | / | 0.307719 |
| | = | 1.106 |
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) |
| = | (216081 / 410501) | / | (242496 / 461509) |
| = | 0.526384 | / | 0.525442 |
| | = | 1.0018 |
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 - (343459 + 116693) / 618920) | / | (1 - (295491 + 102106) / 531074) |
| = | 0.256524 | / | 0.251334 |
| | = | 1.0206 |
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 |
| = | 461509 | / | 410501 |
| | = | 1.1243 |
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)) |
| = | (31807 / (31807 + 102106)) | / | (35888 / (35888 + 116693)) |
| = | 0.23752 | / | 0.235206 |
| | = | 1.0098 |
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) |
| = | (133797 / 461509) | / | (112370 / 410501) |
| = | 0.289912 | / | 0.273739 |
| | = | 1.0591 |
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) |
| = | ((46680 + 118084) / 618920) | / | ((15442 + 111102) / 531074) |
| = | 0.266212 | / | 0.238279 |
| | = | 1.1172 |
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 |
| = | (49637 - 0 | - | 63905) | / | 618920 |
| | = | -0.023053 |
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.
Sysmex has a M-score of -2.42 suggests that the company is unlikely to be a manipulator.
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