RumbleON Beneish M-Score Historical Data
The historical data trend for RumbleON'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.
RumbleON Beneish M-Score Chart
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RumbleON Annual Data
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Trend |
Nov14 |
Nov15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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0.74 |
-4.69 |
-0.10 |
-2.56 |
-2.30 |
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RumbleON 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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-2.56 |
-2.86 |
-2.78 |
-2.74 |
-2.30 |
Competitive Comparison of RumbleON's Beneish M-Score
For the Auto & Truck Dealerships subindustry, RumbleON'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.
RumbleON's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, RumbleON's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where RumbleON's Beneish M-Score falls into.
RumbleON 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 RumbleON 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 * 2.0457 | + | 0.528 * 1.0842 | + | 0.404 * 0.7051 | + | 0.892 * 0.8781 | + | 0.115 * 1.0551 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1003 | + | 4.679 * -0.116712 | - | 0.327 * 1.113 |
| = | -2.30 |
* 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 $50 Mil.
Revenue was 311.174 + 338.111 + 382.731 + 346.304 = $1,378 Mil.
Gross Profit was 71.253 + 91.945 + 106.401 + 91.035 = $361 Mil.
Total Current Assets was $481 Mil.
Total Assets was $926 Mil.
Property, Plant and Equipment(Net PPE) was $229 Mil.
Depreciation, Depletion and Amortization(DDA) was $22 Mil.
Selling, General, & Admin. Expense(SGA) was $343 Mil.
Total Current Liabilities was $395 Mil.
Long-Term Debt & Capital Lease Obligation was $421 Mil.
Net Income was -168.526 + -16.484 + -13.588 + -16.902 = $-216 Mil.
Non Operating Income was -68.708 + 0.075 + 0.101 + 0.042 = $-68 Mil.
Cash Flow from Operations was -19.575 + -13.031 + -15.149 + 8.855 = $-39 Mil.
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Total Receivables was $28 Mil.
Revenue was 331.55 + 380.664 + 412.182 + 445.201 = $1,570 Mil.
Gross Profit was 92.446 + 114.443 + 133.141 + 105.213 = $445 Mil.
Total Current Assets was $461 Mil.
Total Assets was $1,027 Mil.
Property, Plant and Equipment(Net PPE) was $225 Mil.
Depreciation, Depletion and Amortization(DDA) was $23 Mil.
Selling, General, & Admin. Expense(SGA) was $355 Mil.
Total Current Liabilities was $312 Mil.
Long-Term Debt & Capital Lease Obligation was $501 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) |
| = | (50.3 / 1378.32) | / | (28 / 1569.597) |
| = | 0.036494 | / | 0.017839 |
| | = | 2.0457 |
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) |
| = | (445.243 / 1569.597) | / | (360.634 / 1378.32) |
| = | 0.283667 | / | 0.261648 |
| | = | 1.0842 |
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 - (480.8 + 228.67) / 926.3) | / | (1 - (460.8 + 225.38) / 1027.2) |
| = | 0.234082 | / | 0.33199 |
| | = | 0.7051 |
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 |
| = | 1378.32 | / | 1569.597 |
| | = | 0.8781 |
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)) |
| = | (23 / (23 + 225.38)) | / | (22 / (22 + 228.67)) |
| = | 0.0926 | / | 0.087765 |
| | = | 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) |
| = | (342.908 / 1378.32) | / | (354.904 / 1569.597) |
| = | 0.248787 | / | 0.226112 |
| | = | 1.1003 |
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) |
| = | ((420.8 + 395) / 926.3) | / | ((501.1 + 311.7) / 1027.2) |
| = | 0.880708 | / | 0.791277 |
| | = | 1.113 |
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 |
| = | (-215.5 - -68.49 | - | -38.9) | / | 926.3 |
| | = | -0.116712 |
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.
RumbleON has a M-score of -2.30 suggests that the company is unlikely to be a manipulator.
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