Walmart Beneish M-Score Historical Data
The historical data trend for Walmart'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.
Walmart Beneish M-Score Chart
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Walmart Annual Data
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Jan15 |
Jan16 |
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Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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-2.73 |
-2.87 |
-2.31 |
-2.83 |
-2.74 |
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Walmart Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
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Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-2.83 |
-2.95 |
-2.90 |
-2.73 |
-2.74 |
Competitive Comparison of Walmart's Beneish M-Score
For the Discount Stores subindustry, Walmart'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.
Walmart's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, Walmart's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Walmart's Beneish M-Score falls into.
Walmart 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 Walmart 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 * 1.0826 | + | 0.528 * 0.9905 | + | 0.404 * 0.9012 | + | 0.892 * 1.0132 | + | 0.115 * 1.0408 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9707 | + | 4.679 * -0.066971 | - | 0.327 * 0.9814 |
| = | -2.73 |
* 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 €8,075 Mil.
Revenue was 159170.184 + 152281.388 + 146115.328 + 138898.512 = €596,465 Mil.
Gross Profit was 38154.834 + 37521.087 + 35962.928 + 33759.504 = €145,398 Mil.
Total Current Assets was €70,573 Mil.
Total Assets was €231,702 Mil.
Property, Plant and Equipment(Net PPE) was €119,650 Mil.
Depreciation, Depletion and Amortization(DDA) was €10,910 Mil.
Selling, General, & Admin. Expense(SGA) was €120,561 Mil.
Total Current Liabilities was €84,837 Mil.
Long-Term Debt & Capital Lease Obligation was €50,292 Mil.
Net Income was 5043.492 + 428.991 + 7133.464 + 1525.776 = €14,132 Mil.
Non Operating Income was 746.334 + -4498.25 + 3530.12 + -2731.44 = €-2,953 Mil.
Cash Flow from Operations was 15341.616 + 769.911 + 12265.472 + 4225.296 = €32,602 Mil.
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Total Receivables was €7,362 Mil.
Revenue was 152236.544 + 155105.195 + 150260.397 + 131092.894 = €588,695 Mil.
Gross Profit was 35844 + 37758 + 36391.643 + 32152.572 = €142,146 Mil.
Total Current Assets was €70,208 Mil.
Total Assets was €225,687 Mil.
Property, Plant and Equipment(Net PPE) was €110,649 Mil.
Depreciation, Depletion and Amortization(DDA) was €10,540 Mil.
Selling, General, & Admin. Expense(SGA) was €122,588 Mil.
Total Current Liabilities was €85,560 Mil.
Long-Term Debt & Capital Lease Obligation was €48,553 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) |
| = | (8074.728 / 596465.412) | / | (7361.824 / 588695.03) |
| = | 0.013538 | / | 0.012505 |
| | = | 1.0826 |
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) |
| = | (142146.215 / 588695.03) | / | (145398.353 / 596465.412) |
| = | 0.24146 | / | 0.243767 |
| | = | 0.9905 |
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 - (70573.086 + 119650.284) / 231702.282) | / | (1 - (70207.84 + 110649.152) / 225686.816) |
| = | 0.179018 | / | 0.198637 |
| | = | 0.9012 |
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 |
| = | 596465.412 | / | 588695.03 |
| | = | 1.0132 |
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)) |
| = | (10539.73 / (10539.73 + 110649.152)) | / | (10909.908 / (10909.908 + 119650.284)) |
| = | 0.086969 | / | 0.083562 |
| | = | 1.0408 |
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) |
| = | (120561.343 / 596465.412) | / | (122588.232 / 588695.03) |
| = | 0.202126 | / | 0.208237 |
| | = | 0.9707 |
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) |
| = | ((50291.712 + 84836.97) / 231702.282) | / | ((48552.96 + 85559.744) / 225686.816) |
| = | 0.5832 | / | 0.594243 |
| | = | 0.9814 |
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 |
| = | (14131.723 - -2953.236 | - | 32602.295) | / | 231702.282 |
| | = | -0.066971 |
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.
Walmart has a M-score of -2.73 suggests that the company is unlikely to be a manipulator.
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