AutoCanada Beneish M-Score Historical Data
The historical data trend for AutoCanada'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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AutoCanada 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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-2.86 |
-2.86 |
-2.25 |
-2.08 |
-2.55 |
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AutoCanada 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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-2.08 |
-2.43 |
-2.45 |
-2.42 |
-2.55 |
Competitive Comparison
For the Auto & Truck Dealerships subindustry, AutoCanada'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.
AutoCanada Beneish M-Score Distribution
For the Vehicles & Parts industry and Consumer Cyclical sector, AutoCanada's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AutoCanada's Beneish M-Score falls into.
AutoCanada 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 AutoCanada 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 * 1.0973 | + | 0.528 * 0.9906 | + | 0.404 * 0.9452 | + | 0.892 * 1.0349 | + | 0.115 * 0.9672 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0569 | + | 4.679 * -0.029413 | - | 0.327 * 0.9837 |
| = | -2.53 |
* 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 $182 Mil.
Revenue was 1105.988 + 1224.907 + 1321.889 + 1124.992 = $4,778 Mil.
Gross Profit was 192.19 + 214.489 + 239.905 + 186.349 = $833 Mil.
Total Current Assets was $1,148 Mil.
Total Assets was $2,355 Mil.
Property, Plant and Equipment(Net PPE) was $584 Mil.
Depreciation, Depletion and Amortization(DDA) was $44 Mil.
Selling, General, & Admin. Expense(SGA) was $634 Mil.
Total Current Liabilities was $1,102 Mil.
Long-Term Debt & Capital Lease Obligation was $769 Mil.
Net Income was -14.741 + 14.705 + 32.035 + 5.706 = $38 Mil.
Non Operating Income was 10.028 + 2.632 + 4.643 + 1.143 = $18 Mil.
Cash Flow from Operations was -14.798 + 22.931 + 41.401 + 38.993 = $89 Mil.
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Total Receivables was $160 Mil.
Revenue was 1021.867 + 1217.444 + 1316.796 + 1060.378 = $4,616 Mil.
Gross Profit was 178.596 + 205.138 + 218.118 + 195.37 = $797 Mil.
Total Current Assets was $969 Mil.
Total Assets was $2,104 Mil.
Property, Plant and Equipment(Net PPE) was $546 Mil.
Depreciation, Depletion and Amortization(DDA) was $40 Mil.
Selling, General, & Admin. Expense(SGA) was $579 Mil.
Total Current Liabilities was $955 Mil.
Long-Term Debt & Capital Lease Obligation was $745 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) |
| = | (182.156 / 4777.776) | / | (160.4 / 4616.485) |
| = | 0.038126 | / | 0.034745 |
| | = | 1.0973 |
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) |
| = | (797.222 / 4616.485) | / | (832.933 / 4777.776) |
| = | 0.17269 | / | 0.174335 |
| | = | 0.9906 |
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 - (1147.578 + 583.91) / 2354.978) | / | (1 - (968.548 + 546.162) / 2104.035) |
| = | 0.264754 | / | 0.280093 |
| | = | 0.9452 |
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 |
| = | 4777.776 | / | 4616.485 |
| | = | 1.0349 |
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)) |
| = | (39.678 / (39.678 + 546.162)) | / | (43.969 / (43.969 + 583.91)) |
| = | 0.067728 | / | 0.070028 |
| | = | 0.9672 |
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) |
| = | (633.684 / 4777.776) | / | (579.308 / 4616.485) |
| = | 0.132632 | / | 0.125487 |
| | = | 1.0569 |
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) |
| = | ((768.628 + 1102.463) / 2354.978) | / | ((744.543 + 954.935) / 2104.035) |
| = | 0.794526 | / | 0.807723 |
| | = | 0.9837 |
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 |
| = | (37.705 - 18.446 | - | 88.527) | / | 2354.978 |
| | = | -0.029413 |
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.
AutoCanada has a M-score of -2.53 suggests that the company is unlikely to be a manipulator.
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