goeasy Beneish M-Score Historical Data
The historical data trend for goeasy'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.
goeasy Beneish M-Score Chart
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goeasy Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-0.90 |
-1.82 |
-0.80 |
-0.89 |
-1.11 |
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goeasy Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-0.85 |
-0.93 |
-1.03 |
-1.11 |
-1.12 |
Competitive Comparison of goeasy's Beneish M-Score
For the Credit Services subindustry, goeasy'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.
goeasy's Beneish M-Score Distribution in the Credit Services Industry
For the Credit Services industry and Financial Services sector, goeasy's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where goeasy's Beneish M-Score falls into.
goeasy 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 goeasy 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 * 1.0513 | + | 0.528 * 1.0127 | + | 0.404 * 0.7712 | + | 0.892 * 1.2284 | + | 0.115 * 0.943 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8633 | + | 4.679 * 0.251813 | - | 0.327 * 1.0071 |
| = | -1.12 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was C$3,631 Mil.
Revenue was 357.114 + 338.112 + 321.732 + 302.928 = C$1,320 Mil.
Gross Profit was 244.181 + 226.113 + 223.529 + 207.466 = C$901 Mil.
Total Current Assets was C$3,834 Mil.
Total Assets was C$4,416 Mil.
Property, Plant and Equipment(Net PPE) was C$137 Mil.
Depreciation, Depletion and Amortization(DDA) was C$86 Mil.
Selling, General, & Admin. Expense(SGA) was C$99 Mil.
Total Current Liabilities was C$156 Mil.
Long-Term Debt & Capital Lease Obligation was C$3,114 Mil.
Net Income was 58.944 + 74.602 + 66.31 + 55.55 = C$255 Mil.
Non Operating Income was -109.593 + -90.26 + -85.391 + -82.304 = C$-368 Mil.
Cash Flow from Operations was -129.735 + -129.784 + -96.488 + -133.054 = C$-489 Mil.
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Total Receivables was C$2,811 Mil.
Revenue was 287.297 + 273.326 + 262.216 + 251.652 = C$1,074 Mil.
Gross Profit was 194.478 + 190.7 + 181.552 + 176.3 = C$743 Mil.
Total Current Assets was C$2,893 Mil.
Total Assets was C$3,494 Mil.
Property, Plant and Equipment(Net PPE) was C$144 Mil.
Depreciation, Depletion and Amortization(DDA) was C$82 Mil.
Selling, General, & Admin. Expense(SGA) was C$94 Mil.
Total Current Liabilities was C$118 Mil.
Long-Term Debt & Capital Lease Obligation was C$2,452 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) |
| = | (3630.63 / 1319.886) | / | (2811.417 / 1074.491) |
| = | 2.750715 | / | 2.616511 |
| | = | 1.0513 |
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) |
| = | (743.03 / 1074.491) | / | (901.289 / 1319.886) |
| = | 0.691518 | / | 0.682854 |
| | = | 1.0127 |
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 - (3834.071 + 136.831) / 4416.028) | / | (1 - (2893.306 + 144.04) / 3494.058) |
| = | 0.100798 | / | 0.130711 |
| | = | 0.7712 |
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 |
| = | 1319.886 | / | 1074.491 |
| | = | 1.2284 |
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)) |
| = | (82.091 / (82.091 + 144.04)) | / | (85.652 / (85.652 + 136.831)) |
| = | 0.363024 | / | 0.384982 |
| | = | 0.943 |
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) |
| = | (99.253 / 1319.886) | / | (93.594 / 1074.491) |
| = | 0.075198 | / | 0.087105 |
| | = | 0.8633 |
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) |
| = | ((3114.367 + 155.99) / 4416.028) | / | ((2451.558 + 117.778) / 3494.058) |
| = | 0.740565 | / | 0.735344 |
| | = | 1.0071 |
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 |
| = | (255.406 - -367.548 | - | -489.061) | / | 4416.028 |
| | = | 0.251813 |
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.
goeasy has a M-score of -1.12 signals that the company is likely to be a manipulator.
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