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 |
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Jan20 |
Jan21 |
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Jan23 |
Jan24 |
| Beneish M-Score |
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-3.19 |
-3.31 |
-2.65 |
-1.89 |
-2.58 |
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Oxford Industries Quarterly Data
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Jan20 |
Apr20 |
Jul20 |
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Apr21 |
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Oct24 |
| Beneish M-Score |
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-2.72 |
-2.58 |
-2.80 |
-2.77 |
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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 * 1.2137 | + | 0.528 * 1.0059 | + | 0.404 * 0.7483 | + | 0.892 * 0.9877 | + | 0.115 * 1.1546 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0789 | + | 4.679 * -0.040709 | - | 0.327 * 1.1003 |
| = | -2.61 |
* 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 (Oct24) TTM: | Last Year (Oct23) TTM: |
Total Receivables was $95 Mil.
Revenue was 308.025 + 419.886 + 398.184 + 404.429 = $1,531 Mil.
Gross Profit was 194.514 + 265.011 + 258.361 + 246.308 = $964 Mil.
Total Current Assets was $307 Mil.
Total Assets was $1,223 Mil.
Property, Plant and Equipment(Net PPE) was $573 Mil.
Depreciation, Depletion and Amortization(DDA) was $68 Mil.
Selling, General, & Admin. Expense(SGA) was $852 Mil.
Total Current Liabilities was $217 Mil.
Long-Term Debt & Capital Lease Obligation was $368 Mil.
Net Income was -3.937 + 40.642 + 38.373 + -60.07 = $15 Mil.
Non Operating Income was 0 + 0 + 0 + -113.611 = $-114 Mil.
Cash Flow from Operations was -18.213 + 88.815 + 32.923 + 74.886 = $178 Mil.
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Total Receivables was $80 Mil.
Revenue was 326.63 + 420.319 + 420.097 + 382.484 = $1,550 Mil.
Gross Profit was 205.419 + 268.729 + 275.129 + 232.635 = $982 Mil.
Total Current Assets was $291 Mil.
Total Assets was $1,162 Mil.
Property, Plant and Equipment(Net PPE) was $435 Mil.
Depreciation, Depletion and Amortization(DDA) was $61 Mil.
Selling, General, & Admin. Expense(SGA) was $800 Mil.
Total Current Liabilities was $213 Mil.
Long-Term Debt & Capital Lease Obligation was $292 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) |
| = | (95.368 / 1530.524) | / | (79.555 / 1549.53) |
| = | 0.062311 | / | 0.051341 |
| | = | 1.2137 |
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) |
| = | (981.912 / 1549.53) | / | (964.194 / 1530.524) |
| = | 0.633684 | / | 0.629976 |
| | = | 1.0059 |
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 - (307.103 + 572.883) / 1223.133) | / | (1 - (291.379 + 435.085) / 1162.156) |
| = | 0.280548 | / | 0.3749 |
| | = | 0.7483 |
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 |
| = | 1530.524 | / | 1549.53 |
| | = | 0.9877 |
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)) |
| = | (60.636 / (60.636 + 435.085)) | / | (67.883 / (67.883 + 572.883)) |
| = | 0.122319 | / | 0.10594 |
| | = | 1.1546 |
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) |
| = | (852.178 / 1530.524) | / | (799.632 / 1549.53) |
| = | 0.556788 | / | 0.516048 |
| | = | 1.0789 |
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) |
| = | ((368.207 + 216.587) / 1223.133) | / | ((292.457 + 212.512) / 1162.156) |
| = | 0.478112 | / | 0.434511 |
| | = | 1.1003 |
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 |
| = | (15.008 - -113.611 | - | 178.411) | / | 1223.133 |
| | = | -0.040709 |
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 -2.61 suggests that the company is unlikely to be a manipulator.
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