Advance Auto Parts Beneish M-Score Historical Data
The historical data trend for Advance Auto Parts'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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Advance Auto Parts Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
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-2.47 |
-2.61 |
-2.67 |
-2.72 |
-2.41 |
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Advance Auto Parts 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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|
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-2.72 |
-2.68 |
-2.60 |
-2.49 |
-2.41 |
Competitive Comparison
For the Specialty Retail subindustry, Advance Auto Parts'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.
Advance Auto Parts Beneish M-Score Distribution
For the Retail - Cyclical industry and Consumer Cyclical sector, Advance Auto Parts's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Advance Auto Parts's Beneish M-Score falls into.
Advance Auto Parts 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 Advance Auto Parts 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 * 1.1559 | + | 0.528 * 1.1052 | + | 0.404 * 0.9753 | + | 0.892 * 1.0119 | + | 0.115 * 0.9164 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0279 | + | 4.679 * -0.022322 | - | 0.327 * 1.0228 |
| = | -2.41 |
* 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 $800 Mil.
Revenue was 2464.869 + 2719.079 + 2686.066 + 3417.594 = $11,288 Mil.
Gross Profit was 920.964 + 986.659 + 1148.069 + 1470.663 = $4,526 Mil.
Total Current Assets was $6,377 Mil.
Total Assets was $12,276 Mil.
Property, Plant and Equipment(Net PPE) was $4,227 Mil.
Depreciation, Depletion and Amortization(DDA) was $306 Mil.
Selling, General, & Admin. Expense(SGA) was $4,426 Mil.
Total Current Liabilities was $5,307 Mil.
Long-Term Debt & Capital Lease Obligation was $4,002 Mil.
Net Income was -60.51 + -48.633 + 85.362 + 42.651 = $19 Mil.
Non Operating Income was 5.731 + -1.216 + 1.684 + -0.674 = $6 Mil.
Cash Flow from Operations was 256.971 + 194.963 + 214.306 + -378.865 = $287 Mil.
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Total Receivables was $684 Mil.
Revenue was 2473.745 + 2641.341 + 2665.426 + 3374.21 = $11,155 Mil.
Gross Profit was 1072.295 + 1179.247 + 1185.719 + 1506.52 = $4,944 Mil.
Total Current Assets was $6,015 Mil.
Total Assets was $11,986 Mil.
Property, Plant and Equipment(Net PPE) was $4,298 Mil.
Depreciation, Depletion and Amortization(DDA) was $284 Mil.
Selling, General, & Admin. Expense(SGA) was $4,256 Mil.
Total Current Liabilities was $5,421 Mil.
Long-Term Debt & Capital Lease Obligation was $3,467 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) |
| = | (800.141 / 11287.608) | / | (684.048 / 11154.722) |
| = | 0.070887 | / | 0.061324 |
| | = | 1.1559 |
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) |
| = | (4943.781 / 11154.722) | / | (4526.355 / 11287.608) |
| = | 0.443201 | / | 0.401002 |
| | = | 1.1052 |
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 - (6377.021 + 4227.322) / 12276.326) | / | (1 - (6014.817 + 4297.829) / 11986.447) |
| = | 0.136196 | / | 0.139641 |
| | = | 0.9753 |
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 |
| = | 11287.608 | / | 11154.722 |
| | = | 1.0119 |
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)) |
| = | (283.8 / (283.8 + 4297.829)) | / | (306.454 / (306.454 + 4227.322)) |
| = | 0.061943 | / | 0.067594 |
| | = | 0.9164 |
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) |
| = | (4426.4 / 11287.608) | / | (4255.536 / 11154.722) |
| = | 0.392147 | / | 0.381501 |
| | = | 1.0279 |
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) |
| = | ((4002.127 + 5307.405) / 12276.326) | / | ((3466.601 + 5420.851) / 11986.447) |
| = | 0.758332 | / | 0.741458 |
| | = | 1.0228 |
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 |
| = | (18.87 - 5.525 | - | 287.375) | / | 12276.326 |
| | = | -0.022322 |
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.
Advance Auto Parts has a M-score of -2.41 suggests that the company is unlikely to be a manipulator.
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