WPP Beneish M-Score Historical Data
The historical data trend for WPP'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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WPP Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
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|
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-2.65 |
-3.85 |
-2.40 |
-2.39 |
-2.89 |
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WPP Semi-Annual Data
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Jun14 |
Dec14 |
Jun15 |
Dec15 |
Jun16 |
Dec16 |
Jun17 |
Dec17 |
Jun18 |
Dec18 |
Jun19 |
Dec19 |
Jun20 |
Dec20 |
Jun21 |
Dec21 |
Jun22 |
Dec22 |
Jun23 |
Dec23 |
| Beneish M-Score |
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|
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|
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-2.40 |
- |
-2.39 |
- |
-2.89 |
Competitive Comparison
For the Advertising Agencies subindustry, WPP'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.
WPP Beneish M-Score Distribution
For the Media - Diversified industry and Communication Services sector, WPP's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where WPP's Beneish M-Score falls into.
WPP 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 WPP 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 * 0.9053 | + | 0.528 * 1.0368 | + | 0.404 * 1.0123 | + | 0.892 * 1.0692 | + | 0.115 * 0.4861 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.637 | + | 4.679 * -0.042363 | - | 0.327 * 1.011 |
| = | -2.85 |
* 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 $13,924 Mil.
Revenue was $18,791 Mil.
Gross Profit was $3,189 Mil.
Total Current Assets was $17,650 Mil.
Total Assets was $33,699 Mil.
Property, Plant and Equipment(Net PPE) was $2,798 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,487 Mil.
Selling, General, & Admin. Expense(SGA) was $2,516 Mil.
Total Current Liabilities was $20,571 Mil.
Long-Term Debt & Capital Lease Obligation was $7,136 Mil.
Net Income was $140 Mil.
Gross Profit was $0 Mil.
Cash Flow from Operations was $1,567 Mil.
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Total Receivables was $14,385 Mil.
Revenue was $17,575 Mil.
Gross Profit was $3,092 Mil.
Total Current Assets was $18,390 Mil.
Total Assets was $35,107 Mil.
Property, Plant and Equipment(Net PPE) was $3,081 Mil.
Depreciation, Depletion and Amortization(DDA) was $625 Mil.
Selling, General, & Admin. Expense(SGA) was $1,438 Mil.
Total Current Liabilities was $21,569 Mil.
Long-Term Debt & Capital Lease Obligation was $6,979 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) |
| = | (13923.924 / 18790.886) | / | (14384.775 / 17574.543) |
| = | 0.740993 | / | 0.818501 |
| | = | 0.9053 |
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) |
| = | (3092.083 / 17574.543) | / | (3188.608 / 18790.886) |
| = | 0.175941 | / | 0.169689 |
| | = | 1.0368 |
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 - (17650.127 + 2798.354) / 33699.241) | / | (1 - (18390.134 + 3080.633) / 35106.577) |
| = | 0.393206 | / | 0.388412 |
| | = | 1.0123 |
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 |
| = | 18790.886 | / | 17574.543 |
| | = | 1.0692 |
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)) |
| = | (624.97 / (624.97 + 3080.633)) | / | (1486.835 / (1486.835 + 2798.354)) |
| = | 0.168655 | / | 0.346971 |
| | = | 0.4861 |
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) |
| = | (2516.456 / 18790.886) | / | (1437.759 / 17574.543) |
| = | 0.133919 | / | 0.081809 |
| | = | 1.637 |
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) |
| = | ((7135.696 + 20570.633) / 33699.241) | / | ((6979.294 + 21569.184) / 35106.577) |
| = | 0.822165 | / | 0.813195 |
| | = | 1.011 |
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 |
| = | (139.747 - 0 | - | 1567.342) | / | 33699.241 |
| | = | -0.042363 |
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.
WPP has a M-score of -2.85 suggests that the company is unlikely to be a manipulator.
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