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.
Teradyne Beneish M-Score Chart
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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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-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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-2.34 |
-2.52 |
-2.78 |
-2.59 |
-2.71 |
Competitive Comparison of Teradyne's Beneish M-Score
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's Beneish M-Score Distribution in the Semiconductors Industry
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 * 1.0132 | + | 0.528 * 1.0306 | + | 0.404 * 1.0776 | + | 0.892 * 0.8483 | + | 0.115 * 1.0423 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2195 | + | 4.679 * -0.033316 | - | 0.327 * 0.8983 |
| = | -2.71 |
* 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 $422 Mil.
Revenue was 670.599 + 703.732 + 684.437 + 617.529 = $2,676 Mil.
Gross Profit was 379.544 + 398.291 + 402.492 + 356.42 = $1,537 Mil.
Total Current Assets was $2,162 Mil.
Total Assets was $3,487 Mil.
Property, Plant and Equipment(Net PPE) was $519 Mil.
Depreciation, Depletion and Amortization(DDA) was $111 Mil.
Selling, General, & Admin. Expense(SGA) was $577 Mil.
Total Current Liabilities was $660 Mil.
Long-Term Debt & Capital Lease Obligation was $65 Mil.
Net Income was 117.054 + 128.116 + 120.05 + 83.531 = $449 Mil.
Non Operating Income was 1.406 + -12.458 + -7.173 + -2.088 = $-20 Mil.
Cash Flow from Operations was 248.78 + 174.347 + 142.768 + 19.336 = $585 Mil.
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Total Receivables was $491 Mil.
Revenue was 731.836 + 827.073 + 840.766 + 755.37 = $3,155 Mil.
Gross Profit was 420.45 + 485.379 + 506.389 + 454.933 = $1,867 Mil.
Total Current Assets was $2,258 Mil.
Total Assets was $3,501 Mil.
Property, Plant and Equipment(Net PPE) was $492 Mil.
Depreciation, Depletion and Amortization(DDA) was $111 Mil.
Selling, General, & Admin. Expense(SGA) was $558 Mil.
Total Current Liabilities was $746 Mil.
Long-Term Debt & Capital Lease Obligation was $64 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) |
| = | (422.124 / 2676.297) | / | (491.145 / 3155.045) |
| = | 0.157727 | / | 0.15567 |
| | = | 1.0132 |
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) |
| = | (1867.151 / 3155.045) | / | (1536.747 / 2676.297) |
| = | 0.591799 | / | 0.574206 |
| | = | 1.0306 |
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 - (2162.035 + 518.909) / 3486.824) | / | (1 - (2257.915 + 492.417) / 3501.252) |
| = | 0.231122 | / | 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 |
| = | 2676.297 | / | 3155.045 |
| | = | 0.8483 |
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)) |
| = | (110.675 / (110.675 + 492.417)) | / | (110.886 / (110.886 + 518.909)) |
| = | 0.183513 | / | 0.176067 |
| | = | 1.0423 |
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) |
| = | (577.316 / 2676.297) | / | (558.102 / 3155.045) |
| = | 0.215714 | / | 0.176892 |
| | = | 1.2195 |
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) |
| = | ((65.092 + 659.951) / 3486.824) | / | ((64.176 + 746.263) / 3501.252) |
| = | 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 |
| = | (448.751 - -20.313 | - | 585.231) | / | 3486.824 |
| | = | -0.033316 |
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 -2.71 suggests that the company is unlikely to be a manipulator.
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