Conn's Beneish M-Score Historical Data
The historical data trend for Conn's'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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Conn's Annual Data
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Trend |
Jan14 |
Jan15 |
Jan16 |
Jan17 |
Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
| Beneish M-Score |
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|
|
|
|
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-2.66 |
-2.48 |
-3.98 |
-2.63 |
-2.85 |
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Conn's Quarterly Data
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Jan19 |
Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
| Beneish M-Score |
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|
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|
|
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-2.82 |
-2.85 |
-2.86 |
-2.82 |
-2.94 |
Competitive Comparison
For the Specialty Retail subindustry, Conn's'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.
Conn's Beneish M-Score Distribution
For the Retail - Cyclical industry and Consumer Cyclical sector, Conn's's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Conn's's Beneish M-Score falls into.
Conn's 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 Conn's 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 * 1.219 | + | 0.528 * 0.9834 | + | 0.404 * 0.8375 | + | 0.892 * 0.8556 | + | 0.115 * 1.086 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1747 | + | 4.679 * -0.08349 | - | 0.327 * 1.1398 |
| = | -2.94 |
* 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 (Oct23) TTM: | Last Year (Oct22) TTM: |
Total Receivables was $518 Mil.
Revenue was 280.13 + 306.906 + 284.57 + 334.875 = $1,206 Mil.
Gross Profit was 133.768 + 152.921 + 136.637 + 155.583 = $579 Mil.
Total Current Assets was $808 Mil.
Total Assets was $1,726 Mil.
Property, Plant and Equipment(Net PPE) was $550 Mil.
Depreciation, Depletion and Amortization(DDA) was $48 Mil.
Selling, General, & Admin. Expense(SGA) was $534 Mil.
Total Current Liabilities was $239 Mil.
Long-Term Debt & Capital Lease Obligation was $1,077 Mil.
Net Income was -51.297 + -33.517 + -35.38 + -42.803 = $-163 Mil.
Non Operating Income was 0 + 0 + 0.807 + -7.838 = $-7 Mil.
Cash Flow from Operations was -3.353 + -22.542 + 26.148 + -12.083 = $-12 Mil.
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Total Receivables was $497 Mil.
Revenue was 321.2 + 346.632 + 339.821 + 402.488 = $1,410 Mil.
Gross Profit was 151.358 + 163.914 + 161.439 + 188.72 = $665 Mil.
Total Current Assets was $821 Mil.
Total Assets was $1,737 Mil.
Property, Plant and Equipment(Net PPE) was $474 Mil.
Depreciation, Depletion and Amortization(DDA) was $46 Mil.
Selling, General, & Admin. Expense(SGA) was $532 Mil.
Total Current Liabilities was $247 Mil.
Long-Term Debt & Capital Lease Obligation was $915 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) |
| = | (517.893 / 1206.481) | / | (496.568 / 1410.141) |
| = | 0.429259 | / | 0.352141 |
| | = | 1.219 |
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) |
| = | (665.431 / 1410.141) | / | (578.909 / 1206.481) |
| = | 0.47189 | / | 0.479833 |
| | = | 0.9834 |
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 - (808.195 + 550.193) / 1726.392) | / | (1 - (821.17 + 473.842) / 1737.132) |
| = | 0.213164 | / | 0.254511 |
| | = | 0.8375 |
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 |
| = | 1206.481 | / | 1410.141 |
| | = | 0.8556 |
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)) |
| = | (45.569 / (45.569 + 473.842)) | / | (48.354 / (48.354 + 550.193)) |
| = | 0.087732 | / | 0.080786 |
| | = | 1.086 |
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) |
| = | (534.358 / 1206.481) | / | (531.658 / 1410.141) |
| = | 0.442906 | / | 0.377025 |
| | = | 1.1747 |
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) |
| = | ((1077.003 + 239.268) / 1726.392) | / | ((915.083 + 246.917) / 1737.132) |
| = | 0.76244 | / | 0.668919 |
| | = | 1.1398 |
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 |
| = | (-162.997 - -7.031 | - | -11.83) | / | 1726.392 |
| | = | -0.08349 |
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.
Conn's has a M-score of -2.94 suggests that the company is unlikely to be a manipulator.
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