MasTec Beneish M-Score Historical Data
The historical data trend for MasTec'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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MasTec 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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-2.63 |
-3.20 |
-2.44 |
-2.35 |
-2.86 |
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MasTec 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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|
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-2.35 |
-2.21 |
-2.35 |
-2.47 |
-2.86 |
Competitive Comparison
For the Engineering & Construction subindustry, MasTec'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.
MasTec Beneish M-Score Distribution
For the Construction industry and Industrials sector, MasTec's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where MasTec's Beneish M-Score falls into.
MasTec 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 MasTec 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 * 0.8143 | + | 0.528 * 1.0578 | + | 0.404 * 0.9706 | + | 0.892 * 1.2268 | + | 0.115 * 0.8847 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0183 | + | 4.679 * -0.086288 | - | 0.327 * 1.0391 |
| = | -2.86 |
* 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 $3,126 Mil.
Revenue was 3280.083 + 3257.077 + 2874.115 + 2584.659 = $11,996 Mil.
Gross Profit was 367.713 + 399.959 + 389.335 + 225.165 = $1,382 Mil.
Total Current Assets was $3,974 Mil.
Total Assets was $9,374 Mil.
Property, Plant and Equipment(Net PPE) was $2,070 Mil.
Depreciation, Depletion and Amortization(DDA) was $603 Mil.
Selling, General, & Admin. Expense(SGA) was $699 Mil.
Total Current Liabilities was $2,837 Mil.
Long-Term Debt & Capital Lease Obligation was $3,181 Mil.
Net Income was 0.753 + 14.296 + 15.542 + -80.54 = $-50 Mil.
Non Operating Income was 21.824 + 23.41 + 11.004 + 15.353 = $72 Mil.
Cash Flow from Operations was 490.705 + 294.482 + -11.539 + -86.371 = $687 Mil.
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Total Receivables was $3,130 Mil.
Revenue was 3008.361 + 2513.484 + 2301.792 + 1954.4 = $9,778 Mil.
Gross Profit was 371.29 + 325.649 + 273.681 + 221.084 = $1,192 Mil.
Total Current Assets was $3,859 Mil.
Total Assets was $9,293 Mil.
Property, Plant and Equipment(Net PPE) was $2,034 Mil.
Depreciation, Depletion and Amortization(DDA) was $507 Mil.
Selling, General, & Admin. Expense(SGA) was $559 Mil.
Total Current Liabilities was $2,496 Mil.
Long-Term Debt & Capital Lease Obligation was $3,246 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) |
| = | (3126.481 / 11995.934) | / | (3129.586 / 9778.037) |
| = | 0.260628 | / | 0.320063 |
| | = | 0.8143 |
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) |
| = | (1191.704 / 9778.037) | / | (1382.172 / 11995.934) |
| = | 0.121876 | / | 0.11522 |
| | = | 1.0578 |
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 - (3974.253 + 2070.185) / 9373.511) | / | (1 - (3859.127 + 2033.634) / 9293.259) |
| = | 0.355158 | / | 0.36591 |
| | = | 0.9706 |
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 |
| = | 11995.934 | / | 9778.037 |
| | = | 1.2268 |
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)) |
| = | (507.148 / (507.148 + 2033.634)) | / | (603.162 / (603.162 + 2070.185)) |
| = | 0.199603 | / | 0.225621 |
| | = | 0.8847 |
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) |
| = | (698.899 / 11995.934) | / | (559.437 / 9778.037) |
| = | 0.058261 | / | 0.057214 |
| | = | 1.0183 |
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) |
| = | ((3180.931 + 2837.219) / 9373.511) | / | ((3246.243 + 2496.037) / 9293.259) |
| = | 0.642038 | / | 0.617897 |
| | = | 1.0391 |
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 |
| = | (-49.949 - 71.591 | - | 687.277) | / | 9373.511 |
| | = | -0.086288 |
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.
MasTec has a M-score of -2.86 suggests that the company is unlikely to be a manipulator.
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