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 |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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|
|
|
|
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-1.91 |
-2.66 |
-2.63 |
-3.20 |
-2.44 |
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MasTec Quarterly Data
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Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
| Beneish M-Score |
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|
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-2.64 |
-2.44 |
-2.60 |
-2.37 |
-2.44 |
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 in comparison to its industry or sector. The grey bar indicates the Beneish M-Score's extreme value range as defined by GuruFocus.
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 * 1.1424 | + | 0.528 * 1.2471 | + | 0.404 * 0.9402 | + | 0.892 * 1.1028 | + | 0.115 * 1.2283 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.433 | + | 4.679 * -0.0478 | - | 0.327 * 1.0677 |
| = | -2.45 |
* 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 (Sep22) TTM: | Last Year (Sep21) TTM: |
Total Receivables was $2,675 Mil.
Revenue was 2513.484 + 2301.792 + 1954.4 + 1809.367 = $8,579 Mil.
Gross Profit was 325.649 + 273.681 + 221.084 + 250.059 = $1,070 Mil.
Total Current Assets was $3,114 Mil.
Total Assets was $7,476 Mil.
Property, Plant and Equipment(Net PPE) was $1,832 Mil.
Depreciation, Depletion and Amortization(DDA) was $451 Mil.
Selling, General, & Admin. Expense(SGA) was $472 Mil.
Total Current Liabilities was $1,986 Mil.
Long-Term Debt & Capital Lease Obligation was $2,236 Mil.
Net Income was 48.896 + 16.212 + -34.978 + 76.644 = $107 Mil.
Non Operating Income was 5.885 + 12.412 + 3.023 + 29.907 = $51 Mil.
Cash Flow from Operations was 117.13 + -129.977 + 131.518 + 293.977 = $413 Mil.
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Total Receivables was $2,123 Mil.
Revenue was 2404.332 + 1962.658 + 1775.424 + 1636.795 = $7,779 Mil.
Gross Profit was 346.996 + 287.426 + 261.565 + 314.56 = $1,211 Mil.
Total Current Assets was $2,588 Mil.
Total Assets was $6,013 Mil.
Property, Plant and Equipment(Net PPE) was $1,261 Mil.
Depreciation, Depletion and Amortization(DDA) was $404 Mil.
Selling, General, & Admin. Expense(SGA) was $299 Mil.
Total Current Liabilities was $1,704 Mil.
Long-Term Debt & Capital Lease Obligation was $1,477 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) |
| = | (2674.884 / 8579.043) | / | (2123.183 / 7779.209) |
| = | 0.31179282 | / | 0.27293045 |
| | = | 1.1424 |
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) |
| = | (1210.547 / 7779.209) | / | (1070.473 / 8579.043) |
| = | 0.15561312 | / | 0.12477767 |
| | = | 1.2471 |
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 - (3114.275 + 1832.187) / 7475.663) | / | (1 - (2588.419 + 1260.981) / 6013.248) |
| = | 0.33832464 | / | 0.35984679 |
| | = | 0.9402 |
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 |
| = | 8579.043 | / | 7779.209 |
| | = | 1.1028 |
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)) |
| = | (403.848 / (403.848 + 1260.981)) | / | (450.901 / (450.901 + 1832.187)) |
| = | 0.24257626 | / | 0.19749611 |
| | = | 1.2283 |
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) |
| = | (472.218 / 8579.043) | / | (298.814 / 7779.209) |
| = | 0.0550432 | / | 0.03841187 |
| | = | 1.433 |
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) |
| = | ((2236.059 + 1986.483) / 7475.663) | / | ((1476.717 + 1704.308) / 6013.248) |
| = | 0.56483846 | / | 0.5290028 |
| | = | 1.0677 |
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 |
| = | (106.774 - 51.227 | - | 412.648) | / | 7475.663 |
| | = | -0.0478 |
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 -2.45 suggests that the company is unlikely to be a manipulator.
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