Yelp Beneish M-Score Historical Data
The historical data trend for Yelp'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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Yelp Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-4.17 |
-3.52 |
-2.82 |
-2.86 |
-3.44 |
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Yelp 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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-2.86 |
-2.83 |
-2.99 |
-2.94 |
-3.44 |
Competitive Comparison
For the Internet Content & Information subindustry, Yelp'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.
Yelp Beneish M-Score Distribution
For the Interactive Media industry and Communication Services sector, Yelp's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Yelp's Beneish M-Score falls into.
Yelp 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 Yelp 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 * 0.8216 | + | 0.528 * 0.9966 | + | 0.404 * 1.1152 | + | 0.892 * 1.1203 | + | 0.115 * 0.8215 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0109 | + | 4.679 * -0.210476 | - | 0.327 * 0.8319 |
| = | -3.44 |
* 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 $150 Mil.
Revenue was 342.376 + 345.122 + 337.126 + 312.438 = $1,337 Mil.
Gross Profit was 312.76 + 316.752 + 306.942 + 286.379 = $1,223 Mil.
Total Current Assets was $624 Mil.
Total Assets was $1,015 Mil.
Property, Plant and Equipment(Net PPE) was $117 Mil.
Depreciation, Depletion and Amortization(DDA) was $70 Mil.
Selling, General, & Admin. Expense(SGA) was $769 Mil.
Total Current Liabilities was $176 Mil.
Long-Term Debt & Capital Lease Obligation was $48 Mil.
Net Income was 27.406 + 58.216 + 14.729 + -1.178 = $99 Mil.
Non Operating Income was 3.054 + 0.967 + 1.242 + 1.205 = $6 Mil.
Cash Flow from Operations was 79.17 + 104.859 + 48.007 + 74.244 = $306 Mil.
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Total Receivables was $163 Mil.
Revenue was 309.103 + 308.891 + 298.884 + 276.628 = $1,194 Mil.
Gross Profit was 280.62 + 282.086 + 271.896 + 253.199 = $1,088 Mil.
Total Current Assets was $596 Mil.
Total Assets was $1,016 Mil.
Property, Plant and Equipment(Net PPE) was $175 Mil.
Depreciation, Depletion and Amortization(DDA) was $78 Mil.
Selling, General, & Admin. Expense(SGA) was $679 Mil.
Total Current Liabilities was $183 Mil.
Long-Term Debt & Capital Lease Obligation was $87 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) |
| = | (150.254 / 1337.062) | / | (163.24 / 1193.506) |
| = | 0.112376 | / | 0.136774 |
| | = | 0.8216 |
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) |
| = | (1087.801 / 1193.506) | / | (1222.833 / 1337.062) |
| = | 0.911433 | / | 0.914567 |
| | = | 0.9966 |
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 - (624.216 + 117.257) / 1014.723) | / | (1 - (595.992 + 174.616) / 1015.922) |
| = | 0.269285 | / | 0.241469 |
| | = | 1.1152 |
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 |
| = | 1337.062 | / | 1193.506 |
| | = | 1.1203 |
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)) |
| = | (77.662 / (77.662 + 174.616)) | / | (70.268 / (70.268 + 117.257)) |
| = | 0.307843 | / | 0.374713 |
| | = | 0.8215 |
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) |
| = | (769.036 / 1337.062) | / | (679.035 / 1193.506) |
| = | 0.575169 | / | 0.568941 |
| | = | 1.0109 |
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) |
| = | ((48.065 + 175.864) / 1014.723) | / | ((86.661 + 182.824) / 1015.922) |
| = | 0.22068 | / | 0.265262 |
| | = | 0.8319 |
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 |
| = | (99.173 - 6.468 | - | 306.28) | / | 1014.723 |
| | = | -0.210476 |
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.
Yelp has a M-score of -3.44 suggests that the company is unlikely to be a manipulator.
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