Vacasa Beneish M-Score Historical Data
The historical data trend for Vacasa'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.
Vacasa Beneish M-Score Chart
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Vacasa Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-2.76 |
-1.47 |
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Vacasa Quarterly Data
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Dec19 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.76 |
-2.89 |
-2.75 |
-1.71 |
-1.47 |
Competitive Comparison of Vacasa's Beneish M-Score
For the Software - Application subindustry, Vacasa'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.
Vacasa's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Vacasa's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Vacasa's Beneish M-Score falls into.
Vacasa 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 Vacasa 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 * 0.8796 | + | 0.528 * 0.9808 | + | 0.404 * 0.7813 | + | 0.892 * 0.9411 | + | 0.115 * 0.9655 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8802 | + | 4.679 * 0.307271 | - | 0.327 * 1.5674 |
| = | -1.47 |
* 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 $14 Mil.
Revenue was 177.44 + 379.077 + 304.579 + 256.854 = $1,118 Mil.
Gross Profit was 74.835 + 228.288 + 162.453 + 132.723 = $598 Mil.
Total Current Assets was $266 Mil.
Total Assets was $664 Mil.
Property, Plant and Equipment(Net PPE) was $57 Mil.
Depreciation, Depletion and Amortization(DDA) was $78 Mil.
Selling, General, & Admin. Expense(SGA) was $294 Mil.
Total Current Liabilities was $423 Mil.
Long-Term Debt & Capital Lease Obligation was $17 Mil.
Net Income was -43.598 + -228.192 + -3.121 + -23.792 = $-299 Mil.
Non Operating Income was 0.518 + -455.177 + 1.617 + 2.157 = $-451 Mil.
Cash Flow from Operations was -80.142 + -280.631 + 150.43 + 158.636 = $-52 Mil.
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Total Receivables was $17 Mil.
Revenue was 218.158 + 412.184 + 310.348 + 247.26 = $1,188 Mil.
Gross Profit was 101.761 + 238.061 + 158.254 + 125.501 = $624 Mil.
Total Current Assets was $381 Mil.
Total Assets was $1,306 Mil.
Property, Plant and Equipment(Net PPE) was $66 Mil.
Depreciation, Depletion and Amortization(DDA) was $83 Mil.
Selling, General, & Admin. Expense(SGA) was $355 Mil.
Total Current Liabilities was $531 Mil.
Long-Term Debt & Capital Lease Obligation was $22 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) |
| = | (14.242 / 1117.95) | / | (17.204 / 1187.95) |
| = | 0.012739 | / | 0.014482 |
| | = | 0.8796 |
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) |
| = | (623.577 / 1187.95) | / | (598.299 / 1117.95) |
| = | 0.524919 | / | 0.535175 |
| | = | 0.9808 |
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 - (265.845 + 56.717) / 663.548) | / | (1 - (381.363 + 65.543) / 1305.584) |
| = | 0.513883 | / | 0.657696 |
| | = | 0.7813 |
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 |
| = | 1117.95 | / | 1187.95 |
| | = | 0.9411 |
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)) |
| = | (83.335 / (83.335 + 65.543)) | / | (78.247 / (78.247 + 56.717)) |
| = | 0.559754 | / | 0.579762 |
| | = | 0.9655 |
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) |
| = | (293.881 / 1117.95) | / | (354.791 / 1187.95) |
| = | 0.262875 | / | 0.298658 |
| | = | 0.8802 |
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) |
| = | ((17.196 + 422.823) / 663.548) | / | ((21.831 + 530.529) / 1305.584) |
| = | 0.663131 | / | 0.423075 |
| | = | 1.5674 |
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 |
| = | (-298.703 - -450.885 | - | -51.707) | / | 663.548 |
| | = | 0.307271 |
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.
Vacasa has a M-score of -1.47 signals that the company is likely to be a manipulator.
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