Symbotic Beneish M-Score Historical Data
The historical data trend for Symbotic'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.
Symbotic Beneish M-Score Chart
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Symbotic Annual Data
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Trend |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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- |
- |
- |
-1.59 |
2.68 |
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Symbotic Quarterly Data
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Sep19 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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0.31 |
23.68 |
2.68 |
-1.35 |
-1.62 |
Competitive Comparison of Symbotic's Beneish M-Score
For the Specialty Industrial Machinery subindustry, Symbotic'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.
Symbotic's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Symbotic's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Symbotic's Beneish M-Score falls into.
Symbotic 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 Symbotic 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 * 0.9575 | + | 0.528 * 1.0849 | + | 0.404 * 2.1935 | + | 0.892 * 1.6755 | + | 0.115 * 1.1241 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6845 | + | 4.679 * -0.082508 | - | 0.327 * 0.7353 |
| = | -1.62 |
* 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 $302 Mil.
Revenue was 424.301 + 368.45 + 391.888 + 311.837 = $1,496 Mil.
Gross Profit was 44.162 + 70.107 + 58.789 + 52.909 = $226 Mil.
Total Current Assets was $1,484 Mil.
Total Assets was $1,588 Mil.
Property, Plant and Equipment(Net PPE) was $75 Mil.
Depreciation, Depletion and Amortization(DDA) was $14 Mil.
Selling, General, & Admin. Expense(SGA) was $209 Mil.
Total Current Liabilities was $1,091 Mil.
Long-Term Debt & Capital Lease Obligation was $0 Mil.
Net Income was -6.58 + -1.928 + -6.208 + -4.347 = $-19 Mil.
Non Operating Income was 9.812 + 6.199 + 3.661 + 2.937 = $23 Mil.
Cash Flow from Operations was 21.072 + -30.15 + 44.528 + 53.902 = $89 Mil.
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Total Receivables was $188 Mil.
Revenue was 266.854 + 206.312 + 244.412 + 175.552 = $893 Mil.
Gross Profit was 42.847 + 35.194 + 36.729 + 31.544 = $146 Mil.
Total Current Assets was $866 Mil.
Total Assets was $910 Mil.
Property, Plant and Equipment(Net PPE) was $36 Mil.
Depreciation, Depletion and Amortization(DDA) was $7 Mil.
Selling, General, & Admin. Expense(SGA) was $182 Mil.
Total Current Liabilities was $850 Mil.
Long-Term Debt & Capital Lease Obligation was $0 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) |
| = | (301.672 / 1496.476) | / | (188.027 / 893.13) |
| = | 0.201588 | / | 0.210526 |
| | = | 0.9575 |
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) |
| = | (146.314 / 893.13) | / | (225.967 / 1496.476) |
| = | 0.163822 | / | 0.150999 |
| | = | 1.0849 |
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 - (1483.911 + 75.038) / 1588.017) | / | (1 - (866.4 + 35.539) / 909.529) |
| = | 0.018305 | / | 0.008345 |
| | = | 2.1935 |
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 |
| = | 1496.476 | / | 893.13 |
| | = | 1.6755 |
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)) |
| = | (7.361 / (7.361 + 35.539)) | / | (13.517 / (13.517 + 75.038)) |
| = | 0.171585 | / | 0.15264 |
| | = | 1.1241 |
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) |
| = | (208.67 / 1496.476) | / | (181.931 / 893.13) |
| = | 0.139441 | / | 0.2037 |
| | = | 0.6845 |
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) |
| = | ((0 + 1091.053) / 1588.017) | / | ((0 + 849.826) / 909.529) |
| = | 0.687054 | / | 0.934358 |
| | = | 0.7353 |
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 |
| = | (-19.063 - 22.609 | - | 89.352) | / | 1588.017 |
| | = | -0.082508 |
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.
Symbotic has a M-score of -1.62 signals that the company is likely to be a manipulator.
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