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.
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Tetra Tech Annual Data
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Trend |
Sep14 |
Sep15 |
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Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.48 |
-2.43 |
-2.56 |
-2.64 |
-2.38 |
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Tetra Tech 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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-2.54 |
-2.26 |
-2.29 |
-2.38 |
-2.32 |
Competitive Comparison
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 Beneish M-Score Distribution
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 * 0.9393 | + | 0.528 * 1.0599 | + | 0.404 * 1.2118 | + | 0.892 * 1.3716 | + | 0.115 * 0.4987 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0016 | + | 4.679 * -0.021546 | - | 0.327 * 1.2394 |
| = | -2.32 |
* 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 $1,130 Mil.
Revenue was 1228.267 + 1260.612 + 1208.947 + 1158.226 = $4,856 Mil.
Gross Profit was 190.498 + 212.092 + 188.846 + 170.846 = $762 Mil.
Total Current Assets was $1,454 Mil.
Total Assets was $3,951 Mil.
Property, Plant and Equipment(Net PPE) was $254 Mil.
Depreciation, Depletion and Amortization(DDA) was $74 Mil.
Selling, General, & Admin. Expense(SGA) was $328 Mil.
Total Current Liabilities was $1,161 Mil.
Long-Term Debt & Capital Lease Obligation was $1,085 Mil.
Net Income was 74.972 + 53.649 + 60.235 + 42.83 = $232 Mil.
Non Operating Income was 0 + -27.52 + -2.107 + -6.081 = $-36 Mil.
Cash Flow from Operations was 9.246 + 122.41 + 132.93 + 87.932 = $353 Mil.
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Total Receivables was $877 Mil.
Revenue was 894.766 + 902.563 + 890.231 + 852.744 = $3,540 Mil.
Gross Profit was 153.246 + 156.035 + 144.584 + 135.173 = $589 Mil.
Total Current Assets was $1,235 Mil.
Total Assets was $2,731 Mil.
Property, Plant and Equipment(Net PPE) was $217 Mil.
Depreciation, Depletion and Amortization(DDA) was $28 Mil.
Selling, General, & Admin. Expense(SGA) was $239 Mil.
Total Current Liabilities was $871 Mil.
Long-Term Debt & Capital Lease Obligation was $382 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) |
| = | (1129.583 / 4856.052) | / | (876.775 / 3540.304) |
| = | 0.232613 | / | 0.247655 |
| | = | 0.9393 |
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) |
| = | (589.038 / 3540.304) | / | (762.282 / 4856.052) |
| = | 0.166381 | / | 0.156976 |
| | = | 1.0599 |
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 - (1454.041 + 254.484) / 3950.823) | / | (1 - (1234.807 + 217.39) / 2731.48) |
| = | 0.567552 | / | 0.468348 |
| | = | 1.2118 |
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 |
| = | 4856.052 | / | 3540.304 |
| | = | 1.3716 |
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)) |
| = | (27.538 / (27.538 + 217.39)) | / | (74.074 / (74.074 + 254.484)) |
| = | 0.112433 | / | 0.225452 |
| | = | 0.4987 |
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) |
| = | (328.023 / 4856.052) | / | (238.765 / 3540.304) |
| = | 0.067549 | / | 0.067442 |
| | = | 1.0016 |
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) |
| = | ((1084.856 + 1160.995) / 3950.823) | / | ((382.154 + 870.615) / 2731.48) |
| = | 0.568451 | / | 0.458641 |
| | = | 1.2394 |
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 |
| = | (231.686 - -35.708 | - | 352.518) | / | 3950.823 |
| | = | -0.021546 |
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 -2.32 suggests that the company is unlikely to be a manipulator.
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