O'Reilly Automotive Beneish M-Score Historical Data
The historical data trend for O'Reilly Automotive'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.
O'Reilly Automotive Beneish M-Score Chart
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O'Reilly Automotive Annual Data
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Dec14 |
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Dec23 |
| Beneish M-Score |
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-2.54 |
-2.84 |
-2.76 |
-2.68 |
-2.67 |
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O'Reilly Automotive Quarterly Data
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Dec19 |
Mar20 |
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| Beneish M-Score |
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-2.71 |
-2.67 |
-2.50 |
-2.52 |
-2.65 |
Competitive Comparison of O'Reilly Automotive's Beneish M-Score
For the Specialty Retail subindustry, O'Reilly Automotive'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.
O'Reilly Automotive's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, O'Reilly Automotive's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where O'Reilly Automotive's Beneish M-Score falls into.
O'Reilly Automotive 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 O'Reilly Automotive 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 * 0.9499 | + | 0.528 * 0.9988 | + | 0.404 * 1.0171 | + | 0.892 * 1.0525 | + | 0.115 * 0.9547 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0185 | + | 4.679 * -0.03908 | - | 0.327 * 0.9706 |
| = | -2.65 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $556 Mil.
Revenue was 4364.437 + 4272.201 + 3976.24 + 3832.015 = $16,445 Mil.
Gross Profit was 2251.225 + 2168.06 + 2034.172 + 1967.429 = $8,421 Mil.
Total Current Assets was $5,698 Mil.
Total Assets was $14,578 Mil.
Property, Plant and Equipment(Net PPE) was $7,706 Mil.
Depreciation, Depletion and Amortization(DDA) was $452 Mil.
Selling, General, & Admin. Expense(SGA) was $5,190 Mil.
Total Current Liabilities was $8,185 Mil.
Long-Term Debt & Capital Lease Obligation was $7,298 Mil.
Net Income was 665.464 + 622.848 + 547.238 + 552.504 = $2,388 Mil.
Non Operating Income was 4.304 + 1.561 + 3.401 + 6.963 = $16 Mil.
Cash Flow from Operations was 772.015 + 948.859 + 704.215 + 516.429 = $2,942 Mil.
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Total Receivables was $556 Mil.
Revenue was 4203.38 + 4068.991 + 3707.864 + 3644.493 = $15,625 Mil.
Gross Profit was 2160.463 + 2086.582 + 1890.329 + 1853.954 = $7,991 Mil.
Total Current Assets was $5,378 Mil.
Total Assets was $13,552 Mil.
Property, Plant and Equipment(Net PPE) was $7,102 Mil.
Depreciation, Depletion and Amortization(DDA) was $396 Mil.
Selling, General, & Admin. Expense(SGA) was $4,841 Mil.
Total Current Liabilities was $7,831 Mil.
Long-Term Debt & Capital Lease Obligation was $6,998 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) |
| = | (556.25 / 16444.893) | / | (556.381 / 15624.728) |
| = | 0.033825 | / | 0.035609 |
| | = | 0.9499 |
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) |
| = | (7991.328 / 15624.728) | / | (8420.886 / 16444.893) |
| = | 0.511454 | / | 0.512067 |
| | = | 0.9988 |
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 - (5698.287 + 7706.311) / 14577.522) | / | (1 - (5377.712 + 7102.061) / 13551.838) |
| = | 0.080461 | / | 0.079108 |
| | = | 1.0171 |
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 |
| = | 16444.893 | / | 15624.728 |
| | = | 1.0525 |
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)) |
| = | (396.468 / (396.468 + 7102.061)) | / | (451.802 / (451.802 + 7706.311)) |
| = | 0.052873 | / | 0.055381 |
| | = | 0.9547 |
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) |
| = | (5189.643 / 16444.893) | / | (4841.471 / 15624.728) |
| = | 0.315578 | / | 0.30986 |
| | = | 1.0185 |
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) |
| = | ((7297.972 + 8185.165) / 14577.522) | / | ((6998.341 + 7831.082) / 13551.838) |
| = | 1.062124 | / | 1.094274 |
| | = | 0.9706 |
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 |
| = | (2388.054 - 16.229 | - | 2941.518) | / | 14577.522 |
| | = | -0.03908 |
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.
O'Reilly Automotive has a M-score of -2.65 suggests that the company is unlikely to be a manipulator.
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