BIXOLON Co Beneish M-Score Historical Data
The historical data trend for BIXOLON Co'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.
BIXOLON Co Beneish M-Score Chart
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BIXOLON Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.70 |
-3.04 |
-1.24 |
-2.73 |
-2.52 |
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BIXOLON Co Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.09 |
-2.52 |
-2.53 |
-2.43 |
-2.24 |
Competitive Comparison of BIXOLON Co's Beneish M-Score
For the Computer Hardware subindustry, BIXOLON Co'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.
BIXOLON Co's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, BIXOLON Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where BIXOLON Co's Beneish M-Score falls into.
BIXOLON Co 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 BIXOLON Co 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 * 1.3 | + | 0.528 * 1.0501 | + | 0.404 * 1.0114 | + | 0.892 * 1.0128 | + | 0.115 * 1.0013 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1593 | + | 4.679 * -0.028975 | - | 0.327 * 0.7286 |
| = | -2.24 |
* 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 ₩20,333 Mil.
Revenue was 28584.14 + 30316.608 + 25341.882 + 26064.197 = ₩110,307 Mil.
Gross Profit was 11440.477 + 12943.642 + 10560.103 + 10112.197 = ₩45,056 Mil.
Total Current Assets was ₩114,009 Mil.
Total Assets was ₩227,944 Mil.
Property, Plant and Equipment(Net PPE) was ₩35,384 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩6,091 Mil.
Selling, General, & Admin. Expense(SGA) was ₩13,557 Mil.
Total Current Liabilities was ₩16,148 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,823 Mil.
Net Income was 1736.711 + 2775.625 + 1427.899 + 3407.804 = ₩9,348 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 6158.25 + 5417.932 + 224.331 + 4152.131 = ₩15,953 Mil.
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Total Receivables was ₩15,443 Mil.
Revenue was 24815.588 + 26382.546 + 30865.736 + 26847.183 = ₩108,911 Mil.
Gross Profit was 9453.525 + 11085.04 + 13007.607 + 13168.91 = ₩46,715 Mil.
Total Current Assets was ₩121,812 Mil.
Total Assets was ₩235,449 Mil.
Property, Plant and Equipment(Net PPE) was ₩33,411 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,760 Mil.
Selling, General, & Admin. Expense(SGA) was ₩11,546 Mil.
Total Current Liabilities was ₩21,920 Mil.
Long-Term Debt & Capital Lease Obligation was ₩3,555 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) |
| = | (20332.538 / 110306.827) | / | (15443.005 / 108911.053) |
| = | 0.184327 | / | 0.141795 |
| | = | 1.3 |
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) |
| = | (46715.082 / 108911.053) | / | (45056.419 / 110306.827) |
| = | 0.428929 | / | 0.408464 |
| | = | 1.0501 |
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 - (114008.839 + 35383.917) / 227944.038) | / | (1 - (121811.557 + 33410.611) / 235448.829) |
| = | 0.344608 | / | 0.340739 |
| | = | 1.0114 |
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 |
| = | 110306.827 | / | 108911.053 |
| | = | 1.0128 |
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)) |
| = | (5759.954 / (5759.954 + 33410.611)) | / | (6090.647 / (6090.647 + 35383.917)) |
| = | 0.147048 | / | 0.146853 |
| | = | 1.0013 |
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) |
| = | (13557.227 / 110306.827) | / | (11545.936 / 108911.053) |
| = | 0.122905 | / | 0.106013 |
| | = | 1.1593 |
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) |
| = | ((1822.77 + 16147.882) / 227944.038) | / | ((3555.132 + 21920.207) / 235448.829) |
| = | 0.078838 | / | 0.108199 |
| | = | 0.7286 |
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 |
| = | (9348.039 - 0 | - | 15952.644) | / | 227944.038 |
| | = | -0.028975 |
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.
BIXOLON Co has a M-score of -2.24 suggests that the company is unlikely to be a manipulator.
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