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 * 0.7773 | + | 0.528 * 0.9458 | + | 0.404 * 0.9991 | + | 0.892 * 1.1616 | + | 0.115 * 1.0102 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9985 | + | 4.679 * -0.072161 | - | 0.327 * 0.931 |
| = | -2.88 |
* 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 $237 Mil.
Revenue was 366.569 + 381.605 + 398.542 + 390.873 = $1,538 Mil.
Gross Profit was 81.047 + 88.149 + 97.246 + 97.019 = $363 Mil.
Total Current Assets was $367 Mil.
Total Assets was $2,196 Mil.
Property, Plant and Equipment(Net PPE) was $565 Mil.
Depreciation, Depletion and Amortization(DDA) was $79 Mil.
Selling, General, & Admin. Expense(SGA) was $142 Mil.
Total Current Liabilities was $194 Mil.
Long-Term Debt & Capital Lease Obligation was $971 Mil.
Net Income was 17.863 + 26.89 + 28.332 + 28.522 = $102 Mil.
Non Operating Income was 4.423 + 8.701 + 1.062 + 1.382 = $16 Mil.
Cash Flow from Operations was 63.54 + 62.588 + 71.447 + 46.893 = $244 Mil.
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Total Receivables was $263 Mil.
Revenue was 336.504 + 373.301 + 406.71 + 207.134 = $1,324 Mil.
Gross Profit was 61.253 + 73.082 + 101.555 + 60.053 = $296 Mil.
Total Current Assets was $417 Mil.
Total Assets was $2,221 Mil.
Property, Plant and Equipment(Net PPE) was $525 Mil.
Depreciation, Depletion and Amortization(DDA) was $75 Mil.
Selling, General, & Admin. Expense(SGA) was $122 Mil.
Total Current Liabilities was $187 Mil.
Long-Term Debt & Capital Lease Obligation was $1,079 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) |
| = | (237.18 / 1537.589) | / | (262.685 / 1323.649) |
| = | 0.154254 | / | 0.198455 |
| | = | 0.7773 |
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) |
| = | (295.943 / 1323.649) | / | (363.461 / 1537.589) |
| = | 0.223581 | / | 0.236384 |
| | = | 0.9458 |
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 - (366.999 + 565.391) / 2195.505) | / | (1 - (417.416 + 524.895) / 2221.479) |
| = | 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 |
| = | 1537.589 | / | 1323.649 |
| | = | 1.1616 |
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)) |
| = | (74.59 / (74.59 + 524.895)) | / | (79.423 / (79.423 + 565.391)) |
| = | 0.124423 | / | 0.123172 |
| | = | 1.0102 |
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) |
| = | (141.861 / 1537.589) | / | (122.305 / 1323.649) |
| = | 0.092262 | / | 0.0924 |
| | = | 0.9985 |
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) |
| = | ((970.569 + 194.306) / 2195.505) | / | ((1078.824 + 187.24) / 2221.479) |
| = | 0.530573 | / | 0.569919 |
| | = | 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 |
| = | (101.607 - 15.568 | - | 244.468) | / | 2195.505 |
| | = | -0.072161 |
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 -2.88 suggests that the company is unlikely to be a manipulator.
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