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 |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.34 |
-2.75 |
-2.55 |
-2.47 |
-2.59 |
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Sysmex Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.28 |
-2.59 |
-2.71 |
-2.63 |
-2.61 |
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 * 1.0422 | + | 0.528 * 0.9698 | + | 0.404 * 1.029 | + | 0.892 * 1.0859 | + | 0.115 * 0.9827 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0799 | + | 4.679 * -0.040129 | - | 0.327 * 1.1285 |
| = | -2.61 |
* 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132,749 Mil.
Revenue was 113826 + 117347 + 95351 + 111759 = 円438,283 Mil.
Gross Profit was 60759 + 60606 + 50408 + 61216 = 円232,989 Mil.
Total Current Assets was 円304,970 Mil.
Total Assets was 円567,200 Mil.
Property, Plant and Equipment(Net PPE) was 円111,019 Mil.
Depreciation, Depletion and Amortization(DDA) was 円34,420 Mil.
Selling, General, & Admin. Expense(SGA) was 円126,668 Mil.
Total Current Liabilities was 円98,489 Mil.
Long-Term Debt & Capital Lease Obligation was 円42,192 Mil.
Net Income was 12277 + 13565 + 8620 + 10599 = 円45,061 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 8197 + 19328 + 11343 + 28954 = 円67,822 Mil.
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Total Receivables was 円117,305 Mil.
Revenue was 104721 + 107992 + 86029 + 104879 = 円403,621 Mil.
Gross Profit was 56327 + 55577 + 42961 + 53208 = 円208,073 Mil.
Total Current Assets was 円271,839 Mil.
Total Assets was 円501,435 Mil.
Property, Plant and Equipment(Net PPE) was 円99,682 Mil.
Depreciation, Depletion and Amortization(DDA) was 円30,207 Mil.
Selling, General, & Admin. Expense(SGA) was 円108,018 Mil.
Total Current Liabilities was 円94,884 Mil.
Long-Term Debt & Capital Lease Obligation was 円15,326 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) |
| = | (132749 / 438283) | / | (117305 / 403621) |
| = | 0.302884 | / | 0.290632 |
| | = | 1.0422 |
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) |
| = | (208073 / 403621) | / | (232989 / 438283) |
| = | 0.515516 | / | 0.531595 |
| | = | 0.9698 |
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 - (304970 + 111019) / 567200) | / | (1 - (271839 + 99682) / 501435) |
| = | 0.266592 | / | 0.259084 |
| | = | 1.029 |
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 |
| = | 438283 | / | 403621 |
| | = | 1.0859 |
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)) |
| = | (30207 / (30207 + 99682)) | / | (34420 / (34420 + 111019)) |
| = | 0.23256 | / | 0.236663 |
| | = | 0.9827 |
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) |
| = | (126668 / 438283) | / | (108018 / 403621) |
| = | 0.28901 | / | 0.267622 |
| | = | 1.0799 |
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) |
| = | ((42192 + 98489) / 567200) | / | ((15326 + 94884) / 501435) |
| = | 0.248027 | / | 0.219789 |
| | = | 1.1285 |
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 |
| = | (45061 - 0 | - | 67822) | / | 567200 |
| | = | -0.040129 |
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 -2.61 suggests that the company is unlikely to be a manipulator.
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