Avalara Beneish M-Score Historical Data
The historical data trend for Avalara'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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Avalara Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
|
|
|
- |
-3.04 |
-2.51 |
-1.81 |
-2.85 |
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Avalara Quarterly Data
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|
Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
-1.98 |
-2.18 |
-2.85 |
-3.03 |
-2.91 |
Competitive Comparison
For the Software - Application subindustry, Avalara'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.
Avalara Beneish M-Score Distribution
For the Software industry and Technology sector, Avalara's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Avalara's Beneish M-Score falls in comparison to its industry or sector. The grey bar indicates the Beneish M-Score's extreme value range as defined by GuruFocus.
Avalara 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 Avalara 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 * 1.0288 | + | 0.528 * 1.0176 | + | 0.404 * 0.716 | + | 0.892 * 1.3261 | + | 0.115 * 0.7961 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.041 | + | 4.679 * -0.068511 | - | 0.327 * 1.8816 |
| = | -2.91 |
* 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 (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $117.4 Mil.
Revenue was 208.593 + 204.53 + 195.142 + 181.167 = $789.4 Mil.
Gross Profit was 146.521 + 144.404 + 135.184 + 128.127 = $554.2 Mil.
Total Current Assets was $1,712.8 Mil.
Total Assets was $2,644.5 Mil.
Property, Plant and Equipment(Net PPE) was $97.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $43.2 Mil.
Selling, General, & Admin. Expense(SGA) was $510.7 Mil.
Total Current Liabilities was $538.1 Mil.
Long-Term Debt & Capital Lease Obligation was $1,006.6 Mil.
Net Income was -55.848 + -32.557 + -45.434 + -32.546 = $-166.4 Mil.
Non Operating Income was 0.645 + 4.127 + -3.766 + -6.168 = $-5.2 Mil.
Cash Flow from Operations was 6.204 + -23.066 + 25.393 + 11.422 = $20.0 Mil.
|
Total Receivables was $86.1 Mil.
Revenue was 169.067 + 153.601 + 144.76 + 127.879 = $595.3 Mil.
Gross Profit was 119.754 + 109.105 + 103.487 + 92.947 = $425.3 Mil.
Total Current Assets was $852.2 Mil.
Total Assets was $1,680.0 Mil.
Property, Plant and Equipment(Net PPE) was $87.8 Mil.
Depreciation, Depletion and Amortization(DDA) was $28.3 Mil.
Selling, General, & Admin. Expense(SGA) was $370.0 Mil.
Total Current Liabilities was $470.2 Mil.
Long-Term Debt & Capital Lease Obligation was $51.4 Mil.
|
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) |
| = | (117.412 / 789.432) | / | (86.063 / 595.307) |
| = | 0.14873 | / | 0.144569 |
| | = | 1.0288 |
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) |
| = | (425.293 / 595.307) | / | (554.236 / 789.432) |
| = | 0.71441 | / | 0.702069 |
| | = | 1.0176 |
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 - (1712.836 + 97.639) / 2644.468) | / | (1 - (852.241 + 87.794) / 1679.954) |
| = | 0.315373 | / | 0.44044 |
| | = | 0.716 |
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 |
| = | 789.432 | / | 595.307 |
| | = | 1.3261 |
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)) |
| = | (28.335 / (28.335 + 87.794)) | / | (43.151 / (43.151 + 97.639)) |
| = | 0.243996 | / | 0.306492 |
| | = | 0.7961 |
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) |
| = | (510.734 / 789.432) | / | (369.979 / 595.307) |
| = | 0.646964 | / | 0.621493 |
| | = | 1.041 |
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) |
| = | ((1006.649 + 538.126) / 2644.468) | / | ((51.359 + 470.195) / 1679.954) |
| = | 0.584153 | / | 0.310457 |
| | = | 1.8816 |
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 |
| = | (-166.385 - -5.162 | - | 19.953) | / | 2644.468 |
| | = | -0.068511 |
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.
Avalara has a M-score of -2.91 suggests that the company is unlikely to be a manipulator.
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