Oxford Industries Beneish M-Score Historical Data
The historical data trend for Oxford Industries'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.
Oxford Industries Beneish M-Score Chart
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Oxford Industries Annual Data
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Jan15 |
Jan16 |
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Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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-3.19 |
-3.31 |
-2.65 |
-1.89 |
-3.07 |
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Oxford Industries Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
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Jan24 |
| Beneish M-Score |
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-1.89 |
-2.12 |
-2.23 |
-2.72 |
-3.07 |
Competitive Comparison of Oxford Industries's Beneish M-Score
For the Apparel Manufacturing subindustry, Oxford Industries'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.
Oxford Industries's Beneish M-Score Distribution in the Manufacturing - Apparel & Accessories Industry
For the Manufacturing - Apparel & Accessories industry and Consumer Cyclical sector, Oxford Industries's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Oxford Industries's Beneish M-Score falls into.
Oxford Industries 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 Oxford Industries 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 * 1.1742 | + | 0.528 * 0.994 | + | 0.404 * 0.8507 | + | 0.892 * 1.1133 | + | 0.115 * 0.8344 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0653 | + | 4.679 * -0.16722 | - | 0.327 * 0.9127 |
| = | -3.07 |
* 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 $83 Mil.
Revenue was 404.429 + 326.63 + 420.319 + 420.097 = $1,571 Mil.
Gross Profit was 246.308 + 205.419 + 268.729 + 275.129 = $996 Mil.
Total Current Assets was $293 Mil.
Total Assets was $1,098 Mil.
Property, Plant and Equipment(Net PPE) was $459 Mil.
Depreciation, Depletion and Amortization(DDA) was $64 Mil.
Selling, General, & Admin. Expense(SGA) was $821 Mil.
Total Current Liabilities was $241 Mil.
Long-Term Debt & Capital Lease Obligation was $273 Mil.
Net Income was -60.07 + 10.782 + 51.453 + 58.538 = $61 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 74.886 + 16.898 + 99.943 + 52.557 = $244 Mil.
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Total Receivables was $63 Mil.
Revenue was 382.484 + 313.033 + 363.43 + 352.581 = $1,412 Mil.
Gross Profit was 232.635 + 197.694 + 232.149 + 226.377 = $889 Mil.
Total Current Assets was $330 Mil.
Total Assets was $1,189 Mil.
Property, Plant and Equipment(Net PPE) was $418 Mil.
Depreciation, Depletion and Amortization(DDA) was $48 Mil.
Selling, General, & Admin. Expense(SGA) was $692 Mil.
Total Current Liabilities was $270 Mil.
Long-Term Debt & Capital Lease Obligation was $340 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) |
| = | (82.911 / 1571.475) | / | (63.426 / 1411.528) |
| = | 0.05276 | / | 0.044934 |
| | = | 1.1742 |
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) |
| = | (888.855 / 1411.528) | / | (995.585 / 1571.475) |
| = | 0.629711 | / | 0.633535 |
| | = | 0.994 |
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 - (293.115 + 459.071) / 1097.844) | / | (1 - (330.463 + 418.274) / 1188.665) |
| = | 0.314852 | / | 0.370103 |
| | = | 0.8507 |
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 |
| = | 1571.475 | / | 1411.528 |
| | = | 1.1133 |
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)) |
| = | (47.605 / (47.605 + 418.274)) | / | (64.066 / (64.066 + 459.071)) |
| = | 0.102183 | / | 0.122465 |
| | = | 0.8344 |
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) |
| = | (820.705 / 1571.475) | / | (692.004 / 1411.528) |
| = | 0.522251 | / | 0.490252 |
| | = | 1.0653 |
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) |
| = | ((273.007 + 240.644) / 1097.844) | / | ((339.72 + 269.639) / 1188.665) |
| = | 0.467872 | / | 0.512641 |
| | = | 0.9127 |
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 |
| = | (60.703 - 0 | - | 244.284) | / | 1097.844 |
| | = | -0.16722 |
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.
Oxford Industries has a M-score of -3.07 suggests that the company is unlikely to be a manipulator.
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