Teradata Beneish M-Score Historical Data
The historical data trend for Teradata'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.
Teradata Beneish M-Score Chart
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Teradata Annual Data
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Dec15 |
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Dec24 |
| Beneish M-Score |
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-2.77 |
-3.13 |
-3.41 |
-3.25 |
-3.04 |
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Teradata Quarterly Data
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| Beneish M-Score |
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-3.04 |
-3.00 |
-3.14 |
-3.04 |
-2.77 |
Competitive Comparison of Teradata's Beneish M-Score
For the Software - Infrastructure subindustry, Teradata'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.
Teradata's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Teradata's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Teradata's Beneish M-Score falls into.
Teradata 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 Teradata 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 * 1.0561 | + | 0.528 * 1.0033 | + | 0.404 * 1.0094 | + | 0.892 * 0.9347 | + | 0.115 * 1.07 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8652 | + | 4.679 * -0.072489 | - | 0.327 * 0.9468 |
| = | -2.77 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $307 Mil.
Revenue was 418 + 409 + 440 + 436 = $1,703 Mil.
Gross Profit was 248 + 243 + 266 + 265 = $1,022 Mil.
Total Current Assets was $791 Mil.
Total Assets was $1,752 Mil.
Property, Plant and Equipment(Net PPE) was $209 Mil.
Depreciation, Depletion and Amortization(DDA) was $93 Mil.
Selling, General, & Admin. Expense(SGA) was $520 Mil.
Total Current Liabilities was $946 Mil.
Long-Term Debt & Capital Lease Obligation was $497 Mil.
Net Income was 44 + 25 + 32 + 37 = $138 Mil.
Non Operating Income was -4 + -4 + -5 + -6 = $-19 Mil.
Cash Flow from Operations was 8 + 156 + 77 + 43 = $284 Mil.
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Total Receivables was $311 Mil.
Revenue was 465 + 457 + 438 + 462 = $1,822 Mil.
Gross Profit was 284 + 278 + 259 + 276 = $1,097 Mil.
Total Current Assets was $769 Mil.
Total Assets was $1,745 Mil.
Property, Plant and Equipment(Net PPE) was $234 Mil.
Depreciation, Depletion and Amortization(DDA) was $115 Mil.
Selling, General, & Admin. Expense(SGA) was $643 Mil.
Total Current Liabilities was $983 Mil.
Long-Term Debt & Capital Lease Obligation was $535 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) |
| = | (307 / 1703) | / | (311 / 1822) |
| = | 0.18027 | / | 0.170692 |
| | = | 1.0561 |
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) |
| = | (1097 / 1822) | / | (1022 / 1703) |
| = | 0.602086 | / | 0.600117 |
| | = | 1.0033 |
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 - (791 + 209) / 1752) | / | (1 - (769 + 234) / 1745) |
| = | 0.429224 | / | 0.425215 |
| | = | 1.0094 |
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 |
| = | 1703 | / | 1822 |
| | = | 0.9347 |
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)) |
| = | (115 / (115 + 234)) | / | (93 / (93 + 209)) |
| = | 0.329513 | / | 0.307947 |
| | = | 1.07 |
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) |
| = | (520 / 1703) | / | (643 / 1822) |
| = | 0.305344 | / | 0.352909 |
| | = | 0.8652 |
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) |
| = | ((497 + 946) / 1752) | / | ((535 + 983) / 1745) |
| = | 0.82363 | / | 0.869914 |
| | = | 0.9468 |
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 |
| = | (138 - -19 | - | 284) | / | 1752 |
| | = | -0.072489 |
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.
Teradata has a M-score of -2.77 suggests that the company is unlikely to be a manipulator.
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