Synaptics Beneish M-Score Historical Data
The historical data trend for Synaptics'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.
Synaptics Beneish M-Score Chart
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Synaptics Annual Data
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Trend |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
Jun24 |
| Beneish M-Score |
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-3.28 |
-2.87 |
-2.44 |
-3.49 |
-2.36 |
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Synaptics Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.77 |
-3.64 |
-3.18 |
-2.36 |
-1.96 |
Competitive Comparison of Synaptics's Beneish M-Score
For the Semiconductors subindustry, Synaptics'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.
Synaptics's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Synaptics's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Synaptics's Beneish M-Score falls into.
Synaptics 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 Synaptics 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 * 1.4009 | + | 0.528 * 1.0706 | + | 0.404 * 1.0833 | + | 0.892 * 0.8382 | + | 0.115 * 0.962 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1449 | + | 4.679 * 0.041475 | - | 0.327 * 0.9149 |
| = | -1.99 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was €122.4 Mil.
Revenue was 232.188 + 229.835 + 218.316 + 217.329 = €897.7 Mil.
Gross Profit was 108.931 + 105.349 + 101.476 + 99.953 = €415.7 Mil.
Total Current Assets was €1,027.1 Mil.
Total Assets was €2,514.9 Mil.
Property, Plant and Equipment(Net PPE) was €71.6 Mil.
Depreciation, Depletion and Amortization(DDA) was €101.2 Mil.
Selling, General, & Admin. Expense(SGA) was €154.8 Mil.
Total Current Liabilities was €228.8 Mil.
Long-Term Debt & Capital Lease Obligation was €905.1 Mil.
Net Income was -20.813 + 193.511 + -16.652 + -8.253 = €147.8 Mil.
Non Operating Income was -12.794 + -16.165 + 0.184 + -1.192 = €-30.0 Mil.
Cash Flow from Operations was -10.271 + 60.385 + -12.604 + 35.946 = €73.5 Mil.
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Total Receivables was €104.2 Mil.
Revenue was 222.725 + 209.798 + 305.044 + 333.326 = €1,070.9 Mil.
Gross Profit was 100.353 + 93.408 + 160.928 + 176.245 = €530.9 Mil.
Total Current Assets was €1,038.8 Mil.
Total Assets was €2,388.1 Mil.
Property, Plant and Equipment(Net PPE) was €107.9 Mil.
Depreciation, Depletion and Amortization(DDA) was €139.3 Mil.
Selling, General, & Admin. Expense(SGA) was €161.3 Mil.
Total Current Liabilities was €230.0 Mil.
Long-Term Debt & Capital Lease Obligation was €946.8 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) |
| = | (122.356 / 897.668) | / | (104.194 / 1070.893) |
| = | 0.136304 | / | 0.097296 |
| | = | 1.4009 |
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) |
| = | (530.934 / 1070.893) | / | (415.709 / 897.668) |
| = | 0.495786 | / | 0.463099 |
| | = | 1.0706 |
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 - (1027.05 + 71.63) / 2514.871) | / | (1 - (1038.758 + 107.942) / 2388.132) |
| = | 0.563127 | / | 0.519834 |
| | = | 1.0833 |
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 |
| = | 897.668 | / | 1070.893 |
| | = | 0.8382 |
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)) |
| = | (139.295 / (139.295 + 107.942)) | / | (101.238 / (101.238 + 71.63)) |
| = | 0.563407 | / | 0.585638 |
| | = | 0.962 |
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) |
| = | (154.76 / 897.668) | / | (161.252 / 1070.893) |
| = | 0.172402 | / | 0.150577 |
| | = | 1.1449 |
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) |
| = | ((905.055 + 228.764) / 2514.871) | / | ((946.839 + 230.034) / 2388.132) |
| = | 0.450846 | / | 0.492801 |
| | = | 0.9149 |
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 |
| = | (147.793 - -29.967 | - | 73.456) | / | 2514.871 |
| | = | 0.041475 |
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.
Synaptics has a M-score of -1.99 suggests that the company is unlikely to be a manipulator.
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