Monro Beneish M-Score Historical Data
The historical data trend for Monro'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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Monro Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.68 |
-2.70 |
-2.66 |
-2.86 |
-2.39 |
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Monro 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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-3.01 |
-2.39 |
-2.76 |
-2.77 |
-2.67 |
Competitive Comparison
For the Auto Parts subindustry, Monro'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.
Monro Beneish M-Score Distribution
For the Vehicles & Parts industry and Consumer Cyclical sector, Monro's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Monro's Beneish M-Score falls into.
Monro 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 Monro 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 * 1.2161 | + | 0.528 * 0.9754 | + | 0.404 * 1.035 | + | 0.892 * 0.9516 | + | 0.115 * 0.9825 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8117 | + | 4.679 * -0.081057 | - | 0.327 * 1.0073 |
| = | -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 $15 Mil.
Revenue was 317.653 + 322.091 + 326.968 + 310.836 = $1,278 Mil.
Gross Profit was 112.677 + 114.973 + 114.396 + 103.8 = $446 Mil.
Total Current Assets was $272 Mil.
Total Assets was $1,733 Mil.
Property, Plant and Equipment(Net PPE) was $680 Mil.
Depreciation, Depletion and Amortization(DDA) was $73 Mil.
Selling, General, & Admin. Expense(SGA) was $287 Mil.
Total Current Liabilities was $487 Mil.
Long-Term Debt & Capital Lease Obligation was $539 Mil.
Net Income was 12.17 + 12.872 + 8.829 + 0.409 = $34 Mil.
Non Operating Income was 0.062 + 0.034 + 0.058 + 0.318 = $0 Mil.
Cash Flow from Operations was 32.156 + 26.576 + 71.731 + 43.825 = $174 Mil.
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Total Receivables was $13 Mil.
Revenue was 335.193 + 329.818 + 349.535 + 328.03 = $1,343 Mil.
Gross Profit was 113.451 + 116.735 + 122.189 + 104.64 = $457 Mil.
Total Current Assets was $269 Mil.
Total Assets was $1,799 Mil.
Property, Plant and Equipment(Net PPE) was $746 Mil.
Depreciation, Depletion and Amortization(DDA) was $79 Mil.
Selling, General, & Admin. Expense(SGA) was $372 Mil.
Total Current Liabilities was $427 Mil.
Long-Term Debt & Capital Lease Obligation was $629 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) |
| = | (15.242 / 1277.548) | / | (13.172 / 1342.576) |
| = | 0.011931 | / | 0.009811 |
| | = | 1.2161 |
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) |
| = | (457.015 / 1342.576) | / | (445.846 / 1277.548) |
| = | 0.340402 | / | 0.348986 |
| | = | 0.9754 |
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 - (271.694 + 679.581) / 1733.097) | / | (1 - (268.581 + 746.394) / 1799.175) |
| = | 0.451113 | / | 0.435866 |
| | = | 1.035 |
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 |
| = | 1277.548 | / | 1342.576 |
| | = | 0.9516 |
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)) |
| = | (78.916 / (78.916 + 746.394)) | / | (73.273 / (73.273 + 679.581)) |
| = | 0.09562 | / | 0.097327 |
| | = | 0.9825 |
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) |
| = | (287.288 / 1277.548) | / | (371.973 / 1342.576) |
| = | 0.224875 | / | 0.277059 |
| | = | 0.8117 |
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) |
| = | ((538.571 + 486.632) / 1733.097) | / | ((629.24 + 427.349) / 1799.175) |
| = | 0.591544 | / | 0.587263 |
| | = | 1.0073 |
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 |
| = | (34.28 - 0.472 | - | 174.288) | / | 1733.097 |
| | = | -0.081057 |
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.
Monro has a M-score of -2.67 suggests that the company is unlikely to be a manipulator.
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