Wacoal Holdings Beneish M-Score Historical Data
The historical data trend for Wacoal Holdings'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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Wacoal Holdings Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.83 |
-2.94 |
-2.71 |
-2.47 |
-2.66 |
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Wacoal Holdings 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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-2.63 |
-2.66 |
-2.62 |
-2.86 |
-2.73 |
Competitive Comparison
For the Apparel Manufacturing subindustry, Wacoal Holdings'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.
Wacoal Holdings Beneish M-Score Distribution
For the Manufacturing - Apparel & Accessories industry and Consumer Cyclical sector, Wacoal Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Wacoal Holdings's Beneish M-Score falls into.
Wacoal Holdings 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 Wacoal Holdings 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 * 0.9674 | + | 0.528 * 0.9944 | + | 0.404 * 0.9774 | + | 0.892 * 0.9367 | + | 0.115 * 0.8443 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9639 | + | 4.679 * -0.042034 | - | 0.327 * 0.995 |
| = | -2.79 |
* 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 $135 Mil.
Revenue was 321.409 + 313.443 + 345.145 + 334.338 = $1,314 Mil.
Gross Profit was 179.724 + 174.737 + 197.017 + 185.135 = $737 Mil.
Total Current Assets was $775 Mil.
Total Assets was $1,954 Mil.
Property, Plant and Equipment(Net PPE) was $391 Mil.
Depreciation, Depletion and Amortization(DDA) was $94 Mil.
Selling, General, & Admin. Expense(SGA) was $709 Mil.
Total Current Liabilities was $311 Mil.
Long-Term Debt & Capital Lease Obligation was $56 Mil.
Net Income was 3.48 + -49.024 + 20.119 + 3.838 = $-22 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 24.33 + 21.117 + 6.862 + 8.222 = $61 Mil.
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Total Receivables was $149 Mil.
Revenue was 343.899 + 338.341 + 365.977 + 354.899 = $1,403 Mil.
Gross Profit was 188.949 + 191.814 + 214.098 + 187.101 = $782 Mil.
Total Current Assets was $801 Mil.
Total Assets was $2,100 Mil.
Property, Plant and Equipment(Net PPE) was $432 Mil.
Depreciation, Depletion and Amortization(DDA) was $84 Mil.
Selling, General, & Admin. Expense(SGA) was $785 Mil.
Total Current Liabilities was $320 Mil.
Long-Term Debt & Capital Lease Obligation was $77 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) |
| = | (135.302 / 1314.335) | / | (149.302 / 1403.116) |
| = | 0.102943 | / | 0.106407 |
| | = | 0.9674 |
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) |
| = | (781.962 / 1403.116) | / | (736.613 / 1314.335) |
| = | 0.557304 | / | 0.560445 |
| | = | 0.9944 |
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 - (774.725 + 390.786) / 1953.598) | / | (1 - (800.653 + 432.34) / 2099.592) |
| = | 0.403403 | / | 0.412746 |
| | = | 0.9774 |
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 |
| = | 1314.335 | / | 1403.116 |
| | = | 0.9367 |
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)) |
| = | (84.261 / (84.261 + 432.34)) | / | (93.575 / (93.575 + 390.786)) |
| = | 0.163107 | / | 0.193193 |
| | = | 0.8443 |
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) |
| = | (708.703 / 1314.335) | / | (784.939 / 1403.116) |
| = | 0.53921 | / | 0.559426 |
| | = | 0.9639 |
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) |
| = | ((56.473 + 311.429) / 1953.598) | / | ((77.197 + 320.18) / 2099.592) |
| = | 0.18832 | / | 0.189264 |
| | = | 0.995 |
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 |
| = | (-21.587 - 0 | - | 60.531) | / | 1953.598 |
| | = | -0.042034 |
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.
Wacoal Holdings has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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