AutoZone Beneish M-Score Historical Data
The historical data trend for AutoZone'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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AutoZone Annual Data
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Trend |
Aug14 |
Aug15 |
Aug16 |
Aug17 |
Aug18 |
Aug19 |
Aug20 |
Aug21 |
Aug22 |
Aug23 |
| Beneish M-Score |
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|
|
|
|
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-2.60 |
-2.66 |
-2.88 |
-2.46 |
-2.57 |
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AutoZone 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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|
|
|
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|
|
|
|
|
|
|
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-2.58 |
-2.59 |
-2.57 |
- |
- |
Competitive Comparison
For the Specialty Retail subindustry, AutoZone'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.
AutoZone Beneish M-Score Distribution
For the Retail - Cyclical industry and Consumer Cyclical sector, AutoZone's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AutoZone's Beneish M-Score falls into.
AutoZone 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 AutoZone 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 * 0.9595 | + | 0.528 * 1.0034 | + | 0.404 * 1.048 | + | 0.892 * 1.0741 | + | 0.115 * 0.9472 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.025795 | - | 0.327 * 1.0399 |
| = | -2.57 |
* 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 (Aug23) TTM: | Last Year (Aug22) TTM: |
Total Receivables was $520 Mil.
Revenue was $17,457 Mil.
Gross Profit was $9,070 Mil.
Total Current Assets was $6,779 Mil.
Total Assets was $15,986 Mil.
Property, Plant and Equipment(Net PPE) was $8,595 Mil.
Depreciation, Depletion and Amortization(DDA) was $498 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $8,512 Mil.
Long-Term Debt & Capital Lease Obligation was $10,586 Mil.
Net Income was $2,528 Mil.
Gross Profit was $0 Mil.
Cash Flow from Operations was $2,941 Mil.
|
Total Receivables was $505 Mil.
Revenue was $16,252 Mil.
Gross Profit was $8,473 Mil.
Total Current Assets was $6,628 Mil.
Total Assets was $15,275 Mil.
Property, Plant and Equipment(Net PPE) was $8,089 Mil.
Depreciation, Depletion and Amortization(DDA) was $442 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $8,588 Mil.
Long-Term Debt & Capital Lease Obligation was $8,960 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) |
| = | (520.385 / 17457.209) | / | (504.886 / 16252.23) |
| = | 0.029809 | / | 0.031066 |
| | = | 0.9595 |
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) |
| = | (8472.65 / 16252.23) | / | (9070.422 / 17457.209) |
| = | 0.521322 | / | 0.51958 |
| | = | 1.0034 |
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 - (6779.426 + 8594.645) / 15985.878) | / | (1 - (6627.984 + 8089.236) / 15275.043) |
| = | 0.038272 | / | 0.036519 |
| | = | 1.048 |
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 |
| = | 17457.209 | / | 16252.23 |
| | = | 1.0741 |
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)) |
| = | (442.223 / (442.223 + 8089.236)) | / | (497.577 / (497.577 + 8594.645)) |
| = | 0.051834 | / | 0.054726 |
| | = | 0.9472 |
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) |
| = | (0 / 17457.209) | / | (0 / 16252.23) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((10585.595 + 8511.856) / 15985.878) | / | ((8960.065 + 8588.393) / 15275.043) |
| = | 1.194645 | / | 1.148832 |
| | = | 1.0399 |
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 |
| = | (2528.426 - 0 | - | 2940.788) | / | 15985.878 |
| | = | -0.025795 |
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.
AutoZone has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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