Rubicon Technologies Beneish M-Score Historical Data
The historical data trend for Rubicon Technologies'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.
Rubicon Technologies Beneish M-Score Chart
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Rubicon Technologies Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-5.42 |
-2.52 |
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Rubicon Technologies Quarterly Data
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Dec19 |
Sep20 |
Dec20 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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- |
-4.75 |
-2.18 |
-2.52 |
-2.88 |
Competitive Comparison of Rubicon Technologies's Beneish M-Score
For the Software - Application subindustry, Rubicon Technologies'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.
Rubicon Technologies's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Rubicon Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Rubicon Technologies's Beneish M-Score falls into.
Rubicon Technologies 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 Rubicon Technologies 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 * 0.9972 | + | 0.528 * 0.5797 | + | 0.404 * 0.9086 | + | 0.892 * 0.8579 | + | 0.115 * 0.6173 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.2397 | + | 4.679 * -0.0314 | - | 0.327 * 0.9831 |
| = | -2.92 |
* 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 MXN1,853 Mil.
Revenue was 2706.219 + 2896.876 + 2983.108 + 2992.708 = MXN11,579 Mil.
Gross Profit was 143.724 + 232.072 + 243.29 + 212.619 = MXN832 Mil.
Total Current Assets was MXN2,587 Mil.
Total Assets was MXN3,291 Mil.
Property, Plant and Equipment(Net PPE) was MXN14 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN85 Mil.
Selling, General, & Admin. Expense(SGA) was MXN990 Mil.
Total Current Liabilities was MXN3,751 Mil.
Long-Term Debt & Capital Lease Obligation was MXN1,700 Mil.
Net Income was -260.827 + -219.969 + -481.702 + -226.334 = MXN-1,189 Mil.
Non Operating Income was 140.039 + -26.225 + -142.922 + -20.23 = MXN-49 Mil.
Cash Flow from Operations was -94.267 + -5.364 + -509.747 + -426.763 = MXN-1,036 Mil.
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Total Receivables was MXN2,165 Mil.
Revenue was 3227.502 + 3236.2 + 3720.933 + 3311.544 = MXN13,496 Mil.
Gross Profit was 150.617 + 144.231 + 145.733 + 121.412 = MXN562 Mil.
Total Current Assets was MXN2,603 Mil.
Total Assets was MXN3,504 Mil.
Property, Plant and Equipment(Net PPE) was MXN93 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN104 Mil.
Selling, General, & Admin. Expense(SGA) was MXN4,812 Mil.
Total Current Liabilities was MXN4,384 Mil.
Long-Term Debt & Capital Lease Obligation was MXN1,518 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) |
| = | (1852.524 / 11578.911) | / | (2165.343 / 13496.179) |
| = | 0.159991 | / | 0.160441 |
| | = | 0.9972 |
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) |
| = | (561.993 / 13496.179) | / | (831.705 / 11578.911) |
| = | 0.041641 | / | 0.071829 |
| | = | 0.5797 |
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 - (2587.257 + 14.206) / 3291.485) | / | (1 - (2602.576 + 92.63) / 3503.519) |
| = | 0.209639 | / | 0.230715 |
| | = | 0.9086 |
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 |
| = | 11578.911 | / | 13496.179 |
| | = | 0.8579 |
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)) |
| = | (104.163 / (104.163 + 92.63)) | / | (85.425 / (85.425 + 14.206)) |
| = | 0.529302 | / | 0.857414 |
| | = | 0.6173 |
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) |
| = | (989.723 / 11578.911) | / | (4811.936 / 13496.179) |
| = | 0.085476 | / | 0.356541 |
| | = | 0.2397 |
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) |
| = | ((1700.203 + 3750.969) / 3291.485) | / | ((1517.921 + 4383.878) / 3503.519) |
| = | 1.656144 | / | 1.684535 |
| | = | 0.9831 |
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 |
| = | (-1188.832 - -49.338 | - | -1036.141) | / | 3291.485 |
| | = | -0.0314 |
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.
Rubicon Technologies has a M-score of -2.92 suggests that the company is unlikely to be a manipulator.
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