AenzaA Beneish M-Score Historical Data
The historical data trend for AenzaA'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.
AenzaA Beneish M-Score Chart
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AenzaA Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.92 |
-2.66 |
-2.65 |
-2.57 |
-2.79 |
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AenzaA 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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-2.57 |
-2.41 |
-2.65 |
-2.91 |
-2.79 |
Competitive Comparison of AenzaA's Beneish M-Score
For the Engineering & Construction subindustry, AenzaA'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.
AenzaA's Beneish M-Score Distribution in the Construction Industry
For the Construction industry and Industrials sector, AenzaA's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AenzaA's Beneish M-Score falls into.
AenzaA 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 AenzaA 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 * 0.8425 | + | 0.528 * 0.6278 | + | 0.404 * 0.9898 | + | 0.892 * 0.9765 | + | 0.115 * 0.8475 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4547 | + | 4.679 * -0.044448 | - | 0.327 * 0.9639 |
| = | -3.14 |
* 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 $283 Mil.
Revenue was 319.393 + 323.667 + 276.176 + 226.427 = $1,146 Mil.
Gross Profit was 51.556 + 76.384 + 35.766 + 16.812 = $181 Mil.
Total Current Assets was $751 Mil.
Total Assets was $1,581 Mil.
Property, Plant and Equipment(Net PPE) was $91 Mil.
Depreciation, Depletion and Amortization(DDA) was $63 Mil.
Selling, General, & Admin. Expense(SGA) was $19 Mil.
Total Current Liabilities was $683 Mil.
Long-Term Debt & Capital Lease Obligation was $279 Mil.
Net Income was 15.701 + 14.686 + -1.378 + -4.631 = $24 Mil.
Non Operating Income was 0 + -10.059 + 2.106 + 7.031 = $-1 Mil.
Cash Flow from Operations was 43.464 + 27.118 + 35.035 + -10.062 = $96 Mil.
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Total Receivables was $344 Mil.
Revenue was 335.349 + 292.56 + 300.346 + 245.015 = $1,173 Mil.
Gross Profit was 20.962 + 27.527 + 58.804 + 8.775 = $116 Mil.
Total Current Assets was $744 Mil.
Total Assets was $1,577 Mil.
Property, Plant and Equipment(Net PPE) was $89 Mil.
Depreciation, Depletion and Amortization(DDA) was $47 Mil.
Selling, General, & Admin. Expense(SGA) was $13 Mil.
Total Current Liabilities was $703 Mil.
Long-Term Debt & Capital Lease Obligation was $293 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) |
| = | (282.802 / 1145.663) | / | (343.765 / 1173.27) |
| = | 0.246846 | / | 0.292997 |
| | = | 0.8425 |
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) |
| = | (116.068 / 1173.27) | / | (180.518 / 1145.663) |
| = | 0.098927 | / | 0.157566 |
| | = | 0.6278 |
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 - (750.764 + 91.478) / 1580.608) | / | (1 - (743.615 + 89.137) / 1577.085) |
| = | 0.46714 | / | 0.471968 |
| | = | 0.9898 |
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 |
| = | 1145.663 | / | 1173.27 |
| | = | 0.9765 |
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)) |
| = | (47.148 / (47.148 + 89.137)) | / | (63.097 / (63.097 + 91.478)) |
| = | 0.345951 | / | 0.408197 |
| | = | 0.8475 |
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) |
| = | (18.568 / 1145.663) | / | (13.071 / 1173.27) |
| = | 0.016207 | / | 0.011141 |
| | = | 1.4547 |
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) |
| = | ((279.144 + 682.743) / 1580.608) | / | ((292.562 + 703.176) / 1577.085) |
| = | 0.608555 | / | 0.631379 |
| | = | 0.9639 |
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 |
| = | (24.378 - -0.922 | - | 95.555) | / | 1580.608 |
| | = | -0.044448 |
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.
AenzaA has a M-score of -3.14 suggests that the company is unlikely to be a manipulator.
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