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.
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O'Reilly Automotive Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
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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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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-2.68 |
-2.72 |
-2.79 |
-2.71 |
-2.67 |
Competitive Comparison
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 Beneish M-Score Distribution
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 * 0.9991 | + | 0.528 * 0.9994 | + | 0.404 * 0.9397 | + | 0.892 * 1.0973 | + | 0.115 * 0.9705 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0124 | + | 4.679 * -0.050648 | - | 0.327 * 1.0388 |
| = | -2.67 |
* 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 $515 Mil.
Revenue was 3832.015 + 4203.38 + 4068.991 + 3707.864 = $15,812 Mil.
Gross Profit was 1967.429 + 2160.463 + 2086.582 + 1890.329 = $8,105 Mil.
Total Current Assets was $5,558 Mil.
Total Assets was $13,873 Mil.
Property, Plant and Equipment(Net PPE) was $7,238 Mil.
Depreciation, Depletion and Amortization(DDA) was $409 Mil.
Selling, General, & Admin. Expense(SGA) was $4,918 Mil.
Total Current Liabilities was $7,661 Mil.
Long-Term Debt & Capital Lease Obligation was $7,451 Mil.
Net Income was 552.504 + 649.827 + 627.365 + 516.885 = $2,347 Mil.
Non Operating Income was 6.963 + -0.486 + 4.186 + 4.479 = $15 Mil.
Cash Flow from Operations was 516.429 + 866.286 + 937.605 + 713.764 = $3,034 Mil.
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Total Receivables was $470 Mil.
Revenue was 3644.493 + 3798.619 + 3670.737 + 3296.011 = $14,410 Mil.
Gross Profit was 1853.954 + 1934.962 + 1884.718 + 1708.072 = $7,382 Mil.
Total Current Assets was $5,048 Mil.
Total Assets was $12,628 Mil.
Property, Plant and Equipment(Net PPE) was $6,536 Mil.
Depreciation, Depletion and Amortization(DDA) was $358 Mil.
Selling, General, & Admin. Expense(SGA) was $4,427 Mil.
Total Current Liabilities was $7,064 Mil.
Long-Term Debt & Capital Lease Obligation was $6,178 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) |
| = | (515.492 / 15812.25) | / | (470.174 / 14409.86) |
| = | 0.032601 | / | 0.032629 |
| | = | 0.9991 |
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) |
| = | (7381.706 / 14409.86) | / | (8104.803 / 15812.25) |
| = | 0.512268 | / | 0.512565 |
| | = | 0.9994 |
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 - (5558.302 + 7237.534) / 13872.995) | / | (1 - (5048.259 + 6536.308) / 12627.979) |
| = | 0.077644 | / | 0.082627 |
| | = | 0.9397 |
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 |
| = | 15812.25 | / | 14409.86 |
| | = | 1.0973 |
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)) |
| = | (357.933 / (357.933 + 6536.308)) | / | (409.061 / (409.061 + 7237.534)) |
| = | 0.051918 | / | 0.053496 |
| | = | 0.9705 |
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) |
| = | (4918.427 / 15812.25) | / | (4427.215 / 14409.86) |
| = | 0.311052 | / | 0.307235 |
| | = | 1.0124 |
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) |
| = | ((7451.469 + 7661.353) / 13872.995) | / | ((6178.309 + 7063.817) / 12627.979) |
| = | 1.08937 | / | 1.048634 |
| | = | 1.0388 |
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 |
| = | (2346.581 - 15.142 | - | 3034.084) | / | 13872.995 |
| | = | -0.050648 |
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 -2.67 suggests that the company is unlikely to be a manipulator.
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