VF Beneish M-Score Historical Data
The historical data trend for VF'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.
VF Beneish M-Score Chart
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VF Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.61 |
-2.49 |
-2.63 |
-2.16 |
-1.88 |
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VF 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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-1.96 |
-1.88 |
-2.21 |
-2.51 |
-3.18 |
Competitive Comparison of VF's Beneish M-Score
For the Apparel Manufacturing subindustry, VF'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.
VF's Beneish M-Score Distribution in the Manufacturing - Apparel & Accessories Industry
For the Manufacturing - Apparel & Accessories industry and Consumer Cyclical sector, VF's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where VF's Beneish M-Score falls into.
VF 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 VF 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 * 0.9056 | + | 0.528 * 1.0164 | + | 0.404 * 0.9039 | + | 0.892 * 0.9008 | + | 0.115 * 1.6413 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0424 | + | 4.679 * -0.119236 | - | 0.327 * 1.0961 |
| = | -3.21 |
* 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 €1,205 Mil.
Revenue was 2714.58 + 2843.082 + 1925.688 + 2558.799 = €10,042 Mil.
Gross Profit was 1496.922 + 1457.233 + 1016.285 + 1268.394 = €5,239 Mil.
Total Current Assets was €4,526 Mil.
Total Assets was €11,569 Mil.
Property, Plant and Equipment(Net PPE) was €2,043 Mil.
Depreciation, Depletion and Amortization(DDA) was €277 Mil.
Selling, General, & Admin. Expense(SGA) was €4,559 Mil.
Total Current Liabilities was €3,666 Mil.
Long-Term Debt & Capital Lease Obligation was €5,400 Mil.
Net Income was -38.928 + -422.303 + -53.003 + -200.709 = €-715 Mil.
Non Operating Income was -208.22 + -3.289 + -3.292 + -297.914 = €-513 Mil.
Cash Flow from Operations was 1031.632 + -171.317 + 150.98 + 165.95 = €1,177 Mil.
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Total Receivables was €1,477 Mil.
Revenue was 3332.95 + 3111.406 + 2139.469 + 2564.795 = €11,149 Mil.
Gross Profit was 1829.112 + 1598.247 + 1152.808 + 1331.012 = €5,911 Mil.
Total Current Assets was €4,950 Mil.
Total Assets was €13,512 Mil.
Property, Plant and Equipment(Net PPE) was €2,101 Mil.
Depreciation, Depletion and Amortization(DDA) was €512 Mil.
Selling, General, & Admin. Expense(SGA) was €4,855 Mil.
Total Current Liabilities was €4,292 Mil.
Long-Term Debt & Capital Lease Obligation was €5,368 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) |
| = | (1205.065 / 10042.149) | / | (1477.319 / 11148.62) |
| = | 0.120001 | / | 0.132511 |
| | = | 0.9056 |
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) |
| = | (5911.179 / 11148.62) | / | (5238.834 / 10042.149) |
| = | 0.530216 | / | 0.521685 |
| | = | 1.0164 |
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 - (4526.244 + 2042.792) / 11569.307) | / | (1 - (4950.319 + 2101.065) / 13511.752) |
| = | 0.432201 | / | 0.47813 |
| | = | 0.9039 |
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 |
| = | 10042.149 | / | 11148.62 |
| | = | 0.9008 |
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)) |
| = | (511.972 / (511.972 + 2101.065)) | / | (276.918 / (276.918 + 2042.792)) |
| = | 0.19593 | / | 0.119376 |
| | = | 1.6413 |
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) |
| = | (4558.712 / 10042.149) | / | (4854.997 / 11148.62) |
| = | 0.453958 | / | 0.43548 |
| | = | 1.0424 |
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) |
| = | ((5400.214 + 3665.509) / 11569.307) | / | ((5367.759 + 4291.645) / 13511.752) |
| = | 0.783601 | / | 0.714889 |
| | = | 1.0961 |
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 |
| = | (-714.943 - -512.715 | - | 1177.245) | / | 11569.307 |
| | = | -0.119236 |
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.
VF has a M-score of -3.21 suggests that the company is unlikely to be a manipulator.
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