Target Beneish M-Score Historical Data
The historical data trend for Target'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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Target Annual Data
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Trend |
Jan15 |
Jan16 |
Jan17 |
Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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|
|
|
|
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-3.01 |
-2.92 |
-2.49 |
-2.31 |
-3.06 |
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Target Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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-2.31 |
-2.81 |
-2.91 |
-3.03 |
-3.06 |
Competitive Comparison
For the Discount Stores subindustry, Target'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.
Target Beneish M-Score Distribution
For the Retail - Defensive industry and Consumer Defensive sector, Target's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Target's Beneish M-Score falls into.
Target 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 Target 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 * 0.8415 | + | 0.528 * 0.892 | + | 0.404 * 1.0219 | + | 0.892 * 0.9843 | + | 0.115 * 1.0264 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.06 | + | 4.679 * -0.082647 | - | 0.327 * 0.9473 |
| = | -3.06 |
* 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 $1,404 Mil.
Revenue was 31919 + 25398 + 24773 + 25322 = $107,412 Mil.
Gross Profit was 8516 + 7249 + 6975 + 6936 = $29,676 Mil.
Total Current Assets was $17,498 Mil.
Total Assets was $55,356 Mil.
Property, Plant and Equipment(Net PPE) was $36,458 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,801 Mil.
Selling, General, & Admin. Expense(SGA) was $21,554 Mil.
Total Current Liabilities was $19,304 Mil.
Long-Term Debt & Capital Lease Obligation was $18,201 Mil.
Net Income was 1382 + 971 + 835 + 950 = $4,138 Mil.
Non Operating Income was 28 + 25 + 16 + 23 = $92 Mil.
Cash Flow from Operations was 3289 + 1934 + 2133 + 1265 = $8,621 Mil.
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Total Receivables was $1,695 Mil.
Revenue was 31395 + 26518 + 26037 + 25170 = $109,120 Mil.
Gross Profit was 7449 + 6838 + 5895 + 6709 = $26,891 Mil.
Total Current Assets was $17,846 Mil.
Total Assets was $53,335 Mil.
Property, Plant and Equipment(Net PPE) was $34,169 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,700 Mil.
Selling, General, & Admin. Expense(SGA) was $20,658 Mil.
Total Current Liabilities was $19,500 Mil.
Long-Term Debt & Capital Lease Obligation was $18,647 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) |
| = | (1404 / 107412) | / | (1695 / 109120) |
| = | 0.013071 | / | 0.015533 |
| | = | 0.8415 |
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) |
| = | (26891 / 109120) | / | (29676 / 107412) |
| = | 0.246435 | / | 0.276282 |
| | = | 0.892 |
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 - (17498 + 36458) / 55356) | / | (1 - (17846 + 34169) / 53335) |
| = | 0.025291 | / | 0.024749 |
| | = | 1.0219 |
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 |
| = | 107412 | / | 109120 |
| | = | 0.9843 |
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)) |
| = | (2700 / (2700 + 34169)) | / | (2801 / (2801 + 36458)) |
| = | 0.073232 | / | 0.071347 |
| | = | 1.0264 |
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) |
| = | (21554 / 107412) | / | (20658 / 109120) |
| = | 0.200667 | / | 0.189315 |
| | = | 1.06 |
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) |
| = | ((18201 + 19304) / 55356) | / | ((18647 + 19500) / 53335) |
| = | 0.677524 | / | 0.715234 |
| | = | 0.9473 |
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 |
| = | (4138 - 92 | - | 8621) | / | 55356 |
| | = | -0.082647 |
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.
Target has a M-score of -3.06 suggests that the company is unlikely to be a manipulator.
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