MongoDB Beneish M-Score Historical Data
The historical data trend for MongoDB'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.
MongoDB Beneish M-Score Chart
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MongoDB Annual Data
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| Beneish M-Score |
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-2.98 |
-2.72 |
-2.66 |
-2.67 |
-2.75 |
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MongoDB Quarterly Data
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| Beneish M-Score |
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-2.67 |
-2.84 |
-2.71 |
-2.73 |
-2.75 |
Competitive Comparison of MongoDB's Beneish M-Score
For the Software - Infrastructure subindustry, MongoDB'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.
MongoDB's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, MongoDB's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where MongoDB's Beneish M-Score falls into.
MongoDB 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 MongoDB 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 * 0.9015 | + | 0.528 * 0.9728 | + | 0.404 * 1.0529 | + | 0.892 * 1.2528 | + | 0.115 * 0.8919 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8657 | + | 4.679 * -0.104106 | - | 0.327 * 0.8887 |
| = | -2.78 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was €299 Mil.
Revenue was 420.446 + 409.992 + 383.107 + 335.871 = €1,549 Mil.
Gross Profit was 315.205 + 308.608 + 287.882 + 246.998 = €1,159 Mil.
Total Current Assets was €2,280 Mil.
Total Assets was €2,634 Mil.
Property, Plant and Equipment(Net PPE) was €83 Mil.
Depreciation, Depletion and Amortization(DDA) was €30 Mil.
Selling, General, & Admin. Expense(SGA) was €899 Mil.
Total Current Liabilities was €518 Mil.
Long-Term Debt & Capital Lease Obligation was €1,078 Mil.
Net Income was -50.912 + -27.744 + -33.988 + -49.472 = €-162 Mil.
Non Operating Income was -0.986 + 1.099 + -1.686 + 1.043 = €-1 Mil.
Cash Flow from Operations was 50.148 + 36.386 + -22.873 + 49.002 = €113 Mil.
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Total Receivables was €265 Mil.
Revenue was 335.298 + 338.625 + 298.498 + 264.324 = €1,237 Mil.
Gross Profit was 252.557 + 243.569 + 211.721 + 191.897 = €900 Mil.
Total Current Assets was €2,076 Mil.
Total Assets was €2,402 Mil.
Property, Plant and Equipment(Net PPE) was €92 Mil.
Depreciation, Depletion and Amortization(DDA) was €28 Mil.
Selling, General, & Admin. Expense(SGA) was €828 Mil.
Total Current Liabilities was €546 Mil.
Long-Term Debt & Capital Lease Obligation was €1,091 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) |
| = | (298.91 / 1549.416) | / | (264.658 / 1236.745) |
| = | 0.192918 | / | 0.213996 |
| | = | 0.9015 |
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) |
| = | (899.744 / 1236.745) | / | (1158.693 / 1549.416) |
| = | 0.72751 | / | 0.747826 |
| | = | 0.9728 |
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 - (2279.978 + 82.994) / 2634.331) | / | (1 - (2075.55 + 91.904) / 2402.493) |
| = | 0.103009 | / | 0.097831 |
| | = | 1.0529 |
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 |
| = | 1549.416 | / | 1236.745 |
| | = | 1.2528 |
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)) |
| = | (28.125 / (28.125 + 91.904)) | / | (29.574 / (29.574 + 82.994)) |
| = | 0.234318 | / | 0.262721 |
| | = | 0.8919 |
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) |
| = | (898.582 / 1549.416) | / | (828.483 / 1236.745) |
| = | 0.579949 | / | 0.66989 |
| | = | 0.8657 |
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) |
| = | ((1077.907 + 517.954) / 2634.331) | / | ((1091.462 + 546.139) / 2402.493) |
| = | 0.605794 | / | 0.681626 |
| | = | 0.8887 |
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 |
| = | (-162.116 - -0.53 | - | 112.663) | / | 2634.331 |
| | = | -0.104106 |
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.
MongoDB has a M-score of -2.78 suggests that the company is unlikely to be a manipulator.
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