AZZ Beneish M-Score Historical Data
The historical data trend for AZZ'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.
AZZ Beneish M-Score Chart
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AZZ Annual Data
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Trend |
Feb15 |
Feb16 |
Feb17 |
Feb18 |
Feb19 |
Feb20 |
Feb21 |
Feb22 |
Feb23 |
Feb24 |
| Beneish M-Score |
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-4.58 |
-2.17 |
-2.85 |
-1.35 |
-2.88 |
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AZZ Quarterly Data
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May19 |
Aug19 |
Nov19 |
Feb20 |
May20 |
Aug20 |
Nov20 |
Feb21 |
May21 |
Aug21 |
Nov21 |
Feb22 |
May22 |
Aug22 |
Nov22 |
Feb23 |
May23 |
Aug23 |
Nov23 |
Feb24 |
| Beneish M-Score |
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-1.35 |
-1.92 |
-2.26 |
-2.57 |
-2.88 |
Competitive Comparison of AZZ's Beneish M-Score
For the Specialty Business Services subindustry, AZZ'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.
AZZ's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, AZZ's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AZZ's Beneish M-Score falls into.
AZZ 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 AZZ 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 * 0.8079 | + | 0.528 * 0.9468 | + | 0.404 * 0.9991 | + | 0.892 * 1.1092 | + | 0.115 * 1.0446 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0002 | + | 4.679 * -0.071811 | - | 0.327 * 0.931 |
| = | -2.90 |
* 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 (Feb24) TTM: | Last Year (Feb23) TTM: |
Total Receivables was €220 Mil.
Revenue was 339.809 + 352.603 + 365.463 + 359.603 = €1,417 Mil.
Gross Profit was 75.131 + 81.45 + 89.175 + 89.257 = €335 Mil.
Total Current Assets was €340 Mil.
Total Assets was €2,035 Mil.
Property, Plant and Equipment(Net PPE) was €524 Mil.
Depreciation, Depletion and Amortization(DDA) was €73 Mil.
Selling, General, & Admin. Expense(SGA) was €131 Mil.
Total Current Liabilities was €180 Mil.
Long-Term Debt & Capital Lease Obligation was €900 Mil.
Net Income was 16.559 + 24.846 + 25.98 + 26.24 = €94 Mil.
Non Operating Income was 4.1 + 8.04 + 0.974 + 1.271 = €14 Mil.
Cash Flow from Operations was 58.902 + 57.831 + 65.517 + 43.142 = €225 Mil.
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Total Receivables was €245 Mil.
Revenue was 314.295 + 366.208 + 401.423 + 195.949 = €1,278 Mil.
Gross Profit was 57.21 + 71.693 + 100.235 + 56.81 = €286 Mil.
Total Current Assets was €390 Mil.
Total Assets was €2,075 Mil.
Property, Plant and Equipment(Net PPE) was €490 Mil.
Depreciation, Depletion and Amortization(DDA) was €72 Mil.
Selling, General, & Admin. Expense(SGA) was €118 Mil.
Total Current Liabilities was €175 Mil.
Long-Term Debt & Capital Lease Obligation was €1,008 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) |
| = | (219.866 / 1417.478) | / | (245.348 / 1277.875) |
| = | 0.155111 | / | 0.191997 |
| | = | 0.8079 |
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) |
| = | (285.948 / 1277.875) | / | (335.013 / 1417.478) |
| = | 0.223768 | / | 0.236344 |
| | = | 0.9468 |
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 - (340.208 + 524.117) / 2035.233) | / | (1 - (389.867 + 490.252) / 2074.861) |
| = | 0.575319 | / | 0.575818 |
| | = | 0.9991 |
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 |
| = | 1417.478 | / | 1277.875 |
| | = | 1.1092 |
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)) |
| = | (72.002 / (72.002 + 490.252)) | / | (73.233 / (73.233 + 524.117)) |
| = | 0.12806 | / | 0.122596 |
| | = | 1.0446 |
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) |
| = | (130.815 / 1417.478) | / | (117.903 / 1277.875) |
| = | 0.092287 | / | 0.092265 |
| | = | 1.0002 |
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) |
| = | ((899.717 + 180.122) / 2035.233) | / | ((1007.622 + 174.882) / 2074.861) |
| = | 0.530573 | / | 0.56992 |
| | = | 0.931 |
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 |
| = | (93.625 - 14.385 | - | 225.392) | / | 2035.233 |
| | = | -0.071811 |
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.
AZZ has a M-score of -2.90 suggests that the company is unlikely to be a manipulator.
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