Siasun Robot & Automation Co Beneish M-Score Historical Data
The historical data trend for Siasun Robot & Automation Co'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.
Siasun Robot & Automation Co Beneish M-Score Chart
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Siasun Robot & Automation Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.82 |
-2.47 |
-2.04 |
-2.16 |
-2.32 |
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Siasun Robot & Automation Co 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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-2.19 |
-2.05 |
-2.36 |
-2.32 |
-2.42 |
Competitive Comparison of Siasun Robot & Automation Co's Beneish M-Score
For the Specialty Industrial Machinery subindustry, Siasun Robot & Automation Co'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.
Siasun Robot & Automation Co's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Siasun Robot & Automation Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Siasun Robot & Automation Co's Beneish M-Score falls into.
Siasun Robot & Automation Co 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 Siasun Robot & Automation Co 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 * 1.0532 | + | 0.528 * 0.6408 | + | 0.404 * 1.0495 | + | 0.892 * 1.0495 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6059 | + | 4.679 * 0.013531 | - | 0.327 * 0.9914 |
| = | -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 ¥2,027 Mil.
Revenue was 733.321 + 1553.921 + 907.582 + 791.152 = ¥3,986 Mil.
Gross Profit was 98.507 + 227.509 + 141.798 + 86.446 = ¥554 Mil.
Total Current Assets was ¥7,856 Mil.
Total Assets was ¥11,695 Mil.
Property, Plant and Equipment(Net PPE) was ¥1,524 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥185 Mil.
Total Current Liabilities was ¥5,933 Mil.
Long-Term Debt & Capital Lease Obligation was ¥1,151 Mil.
Net Income was -40.371 + 128.143 + -6.374 + -28.705 = ¥53 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0 Mil.
Cash Flow from Operations was -199.584 + 203.107 + -121.005 + 11.935 = ¥-106 Mil.
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Total Receivables was ¥1,834 Mil.
Revenue was 713.94 + 1763.109 + 741.916 + 578.864 = ¥3,798 Mil.
Gross Profit was 94.915 + 143.786 + 49.91 + 49.806 = ¥338 Mil.
Total Current Assets was ¥8,064 Mil.
Total Assets was ¥11,915 Mil.
Property, Plant and Equipment(Net PPE) was ¥1,604 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥291 Mil.
Total Current Liabilities was ¥6,703 Mil.
Long-Term Debt & Capital Lease Obligation was ¥576 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) |
| = | (2027.462 / 3985.976) | / | (1834.201 / 3797.829) |
| = | 0.508649 | / | 0.48296 |
| | = | 1.0532 |
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) |
| = | (338.417 / 3797.829) | / | (554.26 / 3985.976) |
| = | 0.089108 | / | 0.139053 |
| | = | 0.6408 |
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 - (7855.634 + 1524.37) / 11694.937) | / | (1 - (8063.994 + 1603.928) / 11915.188) |
| = | 0.197943 | / | 0.188605 |
| | = | 1.0495 |
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 |
| = | 3985.976 | / | 3797.829 |
| | = | 1.0495 |
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)) |
| = | (0 / (0 + 1603.928)) | / | (0 / (0 + 1524.37)) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (184.956 / 3985.976) | / | (290.851 / 3797.829) |
| = | 0.046402 | / | 0.076583 |
| | = | 0.6059 |
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) |
| = | ((1150.622 + 5932.791) / 11694.937) | / | ((576.171 + 6703.091) / 11915.188) |
| = | 0.605682 | / | 0.610923 |
| | = | 0.9914 |
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 |
| = | (52.693 - 0 | - | -105.547) | / | 11694.937 |
| | = | 0.013531 |
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.
Siasun Robot & Automation Co has a M-score of -2.42 suggests that the company is unlikely to be a manipulator.
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