Teradyne Beneish M-Score Historical Data
The historical data trend for Teradyne'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.
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Teradyne Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.44 |
-2.24 |
-2.42 |
-2.34 |
-2.71 |
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Teradyne 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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|
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-2.34 |
-2.52 |
-2.78 |
-2.59 |
-2.71 |
Competitive Comparison
For the Semiconductor Equipment & Materials subindustry, Teradyne'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.
Teradyne Beneish M-Score Distribution
For the Semiconductors industry and Technology sector, Teradyne's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Teradyne's Beneish M-Score falls into.
Teradyne 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 Teradyne 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 * 1.0113 | + | 0.528 * 1.0303 | + | 0.404 * 1.0776 | + | 0.892 * 0.8256 | + | 0.115 * 1.0398 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2217 | + | 4.679 * -0.033204 | - | 0.327 * 0.8983 |
| = | -2.73 |
* 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 €387 Mil.
Revenue was 614.939 + 659.397 + 631.735 + 576.772 = €2,483 Mil.
Gross Profit was 348.042 + 373.199 + 371.5 + 332.896 = €1,426 Mil.
Total Current Assets was €1,983 Mil.
Total Assets was €3,197 Mil.
Property, Plant and Equipment(Net PPE) was €476 Mil.
Depreciation, Depletion and Amortization(DDA) was €103 Mil.
Selling, General, & Admin. Expense(SGA) was €536 Mil.
Total Current Liabilities was €605 Mil.
Long-Term Debt & Capital Lease Obligation was €60 Mil.
Net Income was 107.339 + 120.045 + 110.806 + 78.018 = €416 Mil.
Non Operating Income was 1.289 + -11.673 + -6.621 + -1.95 = €-19 Mil.
Cash Flow from Operations was 228.131 + 163.363 + 131.775 + 18.06 = €541 Mil.
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Total Receivables was €464 Mil.
Revenue was 690.853 + 835.344 + 795.365 + 685.876 = €3,007 Mil.
Gross Profit was 396.905 + 490.233 + 479.044 + 413.079 = €1,779 Mil.
Total Current Assets was €2,131 Mil.
Total Assets was €3,305 Mil.
Property, Plant and Equipment(Net PPE) was €465 Mil.
Depreciation, Depletion and Amortization(DDA) was €105 Mil.
Selling, General, & Admin. Expense(SGA) was €531 Mil.
Total Current Liabilities was €704 Mil.
Long-Term Debt & Capital Lease Obligation was €61 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) |
| = | (387.088 / 2482.843) | / | (463.641 / 3007.438) |
| = | 0.155905 | / | 0.154165 |
| | = | 1.0113 |
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) |
| = | (1779.261 / 3007.438) | / | (1425.637 / 2482.843) |
| = | 0.59162 | / | 0.574195 |
| | = | 1.0303 |
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 - (1982.586 + 475.84) / 3197.418) | / | (1 - (2131.472 + 464.842) / 3305.182) |
| = | 0.231121 | / | 0.214472 |
| | = | 1.0776 |
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 |
| = | 2482.843 | / | 3007.438 |
| | = | 0.8256 |
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)) |
| = | (105.404 / (105.404 + 464.842)) | / | (102.878 / (102.878 + 475.84)) |
| = | 0.18484 | / | 0.177769 |
| | = | 1.0398 |
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) |
| = | (535.605 / 2482.843) | / | (531.032 / 3007.438) |
| = | 0.215722 | / | 0.176573 |
| | = | 1.2217 |
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) |
| = | ((59.689 + 605.175) / 3197.418) | / | ((60.582 + 704.472) / 3305.182) |
| = | 0.207938 | / | 0.231471 |
| | = | 0.8983 |
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 |
| = | (416.208 - -18.955 | - | 541.329) | / | 3197.418 |
| | = | -0.033204 |
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.
Teradyne has a M-score of -2.73 suggests that the company is unlikely to be a manipulator.
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