Upbound Group Beneish M-Score Historical Data
The historical data trend for Upbound Group'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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Upbound Group Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.32 |
-2.40 |
-1.07 |
-3.40 |
-2.83 |
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Upbound Group 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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-3.40 |
-3.16 |
-3.27 |
-2.99 |
-2.83 |
Competitive Comparison
For the Software - Application subindustry, Upbound Group'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.
Upbound Group Beneish M-Score Distribution
For the Software industry and Technology sector, Upbound Group's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Upbound Group's Beneish M-Score falls into.
Upbound Group 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 Upbound Group 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 * 1.0552 | + | 0.528 * 0.967 | + | 0.404 * 0.92 | + | 0.892 * 0.9404 | + | 0.115 * 1.0551 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0561 | + | 4.679 * -0.064823 | - | 0.327 * 0.9833 |
| = | -2.83 |
* 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 $111 Mil.
Revenue was 1018.091 + 979.098 + 979.163 + 1016.061 = $3,992 Mil.
Gross Profit was 512.602 + 497.166 + 506.226 + 506.264 = $2,022 Mil.
Total Current Assets was $261 Mil.
Total Assets was $2,721 Mil.
Property, Plant and Equipment(Net PPE) was $1,797 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,294 Mil.
Selling, General, & Admin. Expense(SGA) was $815 Mil.
Total Current Liabilities was $452 Mil.
Long-Term Debt & Capital Lease Obligation was $1,600 Mil.
Net Income was -11.254 + 4.363 + -45.618 + 47.33 = $-5 Mil.
Non Operating Income was 0 + -29.057 + 0 + 0 = $-29 Mil.
Cash Flow from Operations was -19.652 + 77.982 + 36.543 + 105.417 = $200 Mil.
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Total Receivables was $112 Mil.
Revenue was 990.459 + 1023.957 + 1071.255 + 1159.722 = $4,245 Mil.
Gross Profit was 495.359 + 505.535 + 532.544 + 546.095 = $2,080 Mil.
Total Current Assets was $309 Mil.
Total Assets was $2,764 Mil.
Property, Plant and Equipment(Net PPE) was $1,723 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,363 Mil.
Selling, General, & Admin. Expense(SGA) was $821 Mil.
Total Current Liabilities was $445 Mil.
Long-Term Debt & Capital Lease Obligation was $1,674 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) |
| = | (111.005 / 3992.413) | / | (111.865 / 4245.393) |
| = | 0.027804 | / | 0.02635 |
| | = | 1.0552 |
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) |
| = | (2079.533 / 4245.393) | / | (2022.258 / 3992.413) |
| = | 0.489833 | / | 0.506525 |
| | = | 0.967 |
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 - (261.367 + 1796.883) / 2721.43) | / | (1 - (309.064 + 1722.51) / 2763.619) |
| = | 0.243688 | / | 0.264886 |
| | = | 0.92 |
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 |
| = | 3992.413 | / | 4245.393 |
| | = | 0.9404 |
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)) |
| = | (1363.007 / (1363.007 + 1722.51)) | / | (1294.051 / (1294.051 + 1796.883)) |
| = | 0.441743 | / | 0.41866 |
| | = | 1.0551 |
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) |
| = | (815.244 / 3992.413) | / | (820.811 / 4245.393) |
| = | 0.204198 | / | 0.193342 |
| | = | 1.0561 |
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) |
| = | ((1600.062 + 452.247) / 2721.43) | / | ((1674.414 + 445.168) / 2763.619) |
| = | 0.754129 | / | 0.766959 |
| | = | 0.9833 |
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 |
| = | (-5.179 - -29.057 | - | 200.29) | / | 2721.43 |
| | = | -0.064823 |
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.
Upbound Group has a M-score of -2.83 suggests that the company is unlikely to be a manipulator.
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