Tetra Tech Beneish M-Score Historical Data
The historical data trend for Tetra Tech'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.
Tetra Tech Beneish M-Score Chart
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Tetra Tech Annual Data
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Trend |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
Sep24 |
| Beneish M-Score |
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-2.43 |
-2.56 |
-2.64 |
-2.38 |
-2.41 |
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Tetra Tech 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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-2.38 |
-2.32 |
-2.51 |
-2.51 |
-2.41 |
Competitive Comparison of Tetra Tech's Beneish M-Score
For the Engineering & Construction subindustry, Tetra Tech'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.
Tetra Tech's Beneish M-Score Distribution in the Construction Industry
For the Construction industry and Industrials sector, Tetra Tech's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Tetra Tech's Beneish M-Score falls into.
Tetra Tech 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 Tetra Tech 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 * 0.9531 | + | 0.528 * 0.9619 | + | 0.404 * 0.9938 | + | 0.892 * 1.1495 | + | 0.115 * 0.8646 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.015 | + | 4.679 * -0.003726 | - | 0.327 * 0.8867 |
| = | -2.41 |
* 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 $1,203 Mil.
Revenue was 1374.474 + 1344.323 + 1251.616 + 1228.267 = $5,199 Mil.
Gross Profit was 245.275 + 223.172 + 207.495 + 190.498 = $866 Mil.
Total Current Assets was $1,527 Mil.
Total Assets was $4,193 Mil.
Property, Plant and Equipment(Net PPE) was $251 Mil.
Depreciation, Depletion and Amortization(DDA) was $74 Mil.
Selling, General, & Admin. Expense(SGA) was $356 Mil.
Total Current Liabilities was $1,220 Mil.
Long-Term Debt & Capital Lease Obligation was $953 Mil.
Net Income was 96.154 + 85.81 + 76.446 + 74.972 = $333 Mil.
Non Operating Income was -9.202 + -0.5 + 0 + 0 = $-10 Mil.
Cash Flow from Operations was 105.598 + 140.929 + 102.935 + 9.246 = $359 Mil.
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Total Receivables was $1,098 Mil.
Revenue was 1260.612 + 1208.947 + 1158.226 + 894.766 = $4,523 Mil.
Gross Profit was 212.092 + 188.846 + 170.846 + 153.246 = $725 Mil.
Total Current Assets was $1,356 Mil.
Total Assets was $3,820 Mil.
Property, Plant and Equipment(Net PPE) was $251 Mil.
Depreciation, Depletion and Amortization(DDA) was $61 Mil.
Selling, General, & Admin. Expense(SGA) was $305 Mil.
Total Current Liabilities was $1,208 Mil.
Long-Term Debt & Capital Lease Obligation was $1,024 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) |
| = | (1203.109 / 5198.68) | / | (1098.097 / 4522.551) |
| = | 0.231426 | / | 0.242805 |
| | = | 0.9531 |
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) |
| = | (725.03 / 4522.551) | / | (866.44 / 5198.68) |
| = | 0.160314 | / | 0.166665 |
| | = | 0.9619 |
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 - (1527.383 + 251.015) / 4192.676) | / | (1 - (1356.024 + 250.764) / 3820.477) |
| = | 0.575832 | / | 0.579427 |
| | = | 0.9938 |
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 |
| = | 5198.68 | / | 4522.551 |
| | = | 1.1495 |
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)) |
| = | (61.206 / (61.206 + 250.764)) | / | (73.677 / (73.677 + 251.015)) |
| = | 0.196192 | / | 0.226914 |
| | = | 0.8646 |
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) |
| = | (356.002 / 5198.68) | / | (305.108 / 4522.551) |
| = | 0.068479 | / | 0.067464 |
| | = | 1.015 |
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) |
| = | ((952.729 + 1219.527) / 4192.676) | / | ((1024.214 + 1208.142) / 3820.477) |
| = | 0.518107 | / | 0.584313 |
| | = | 0.8867 |
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 |
| = | (333.382 - -9.702 | - | 358.708) | / | 4192.676 |
| | = | -0.003726 |
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.
Tetra Tech has a M-score of -2.41 suggests that the company is unlikely to be a manipulator.
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