Bausen Beneish M-Score Historical Data
The historical data trend for Bausen'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.
Bausen Beneish M-Score Chart
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Bausen Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
- |
-2.35 |
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Bausen Quarterly Data
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Dec17 |
Dec18 |
Jun19 |
Dec19 |
Jun20 |
Dec20 |
Jun21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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- |
-2.35 |
-1.98 |
-2.21 |
-2.47 |
Competitive Comparison of Bausen's Beneish M-Score
For the Home Improvement Retail subindustry, Bausen'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.
Bausen's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, Bausen's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Bausen's Beneish M-Score falls into.
Bausen 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 Bausen 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 * 1.0755 | + | 0.528 * 0.8855 | + | 0.404 * 0.6478 | + | 0.892 * 0.9586 | + | 0.115 * 0.8176 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1893 | + | 4.679 * 0.043252 | - | 0.327 * 0.9101 |
| = | -2.47 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was NT$183 Mil.
Revenue was 543.84 + 526.052 + 497.233 + 516.721 = NT$2,084 Mil.
Gross Profit was 219.765 + 234.363 + 221.236 + 231.861 = NT$907 Mil.
Total Current Assets was NT$1,676 Mil.
Total Assets was NT$2,205 Mil.
Property, Plant and Equipment(Net PPE) was NT$461 Mil.
Depreciation, Depletion and Amortization(DDA) was NT$163 Mil.
Selling, General, & Admin. Expense(SGA) was NT$761 Mil.
Total Current Liabilities was NT$829 Mil.
Long-Term Debt & Capital Lease Obligation was NT$330 Mil.
Net Income was 11.011 + 17.599 + 18.904 + 15.564 = NT$63 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = NT$0 Mil.
Cash Flow from Operations was 68.907 + -12.387 + -99.662 + 10.836 = NT$-32 Mil.
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Total Receivables was NT$177 Mil.
Revenue was 578.885 + 575.623 + 514.618 + 504.662 = NT$2,174 Mil.
Gross Profit was 254.738 + 229.529 + 185.475 + 168.313 = NT$838 Mil.
Total Current Assets was NT$1,390 Mil.
Total Assets was NT$1,949 Mil.
Property, Plant and Equipment(Net PPE) was NT$466 Mil.
Depreciation, Depletion and Amortization(DDA) was NT$126 Mil.
Selling, General, & Admin. Expense(SGA) was NT$667 Mil.
Total Current Liabilities was NT$774 Mil.
Long-Term Debt & Capital Lease Obligation was NT$352 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) |
| = | (183.001 / 2083.846) | / | (177.495 / 2173.788) |
| = | 0.087819 | / | 0.081652 |
| | = | 1.0755 |
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) |
| = | (838.055 / 2173.788) | / | (907.225 / 2083.846) |
| = | 0.385527 | / | 0.435361 |
| | = | 0.8855 |
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 - (1676.003 + 461.19) / 2205.304) | / | (1 - (1389.754 + 466.498) / 1949.182) |
| = | 0.030885 | / | 0.047676 |
| | = | 0.6478 |
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 |
| = | 2083.846 | / | 2173.788 |
| | = | 0.9586 |
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)) |
| = | (126.417 / (126.417 + 466.498)) | / | (162.69 / (162.69 + 461.19)) |
| = | 0.213213 | / | 0.260771 |
| | = | 0.8176 |
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) |
| = | (760.814 / 2083.846) | / | (667.321 / 2173.788) |
| = | 0.365101 | / | 0.306985 |
| | = | 1.1893 |
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) |
| = | ((330.322 + 828.938) / 2205.304) | / | ((351.781 + 774.034) / 1949.182) |
| = | 0.525669 | / | 0.577583 |
| | = | 0.9101 |
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 |
| = | (63.078 - 0 | - | -32.306) | / | 2205.304 |
| | = | 0.043252 |
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.
Bausen has a M-score of -2.47 suggests that the company is unlikely to be a manipulator.
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