SillaJen Beneish M-Score Historical Data
The historical data trend for SillaJen'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.
SillaJen Beneish M-Score Chart
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SillaJen Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-3.07 |
-1.96 |
15.84 |
-4.66 |
-2.34 |
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SillaJen Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-4.66 |
-3.93 |
-2.35 |
-1.75 |
-2.34 |
Competitive Comparison of SillaJen's Beneish M-Score
For the Biotechnology subindustry, SillaJen'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.
SillaJen's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, SillaJen's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where SillaJen's Beneish M-Score falls into.
SillaJen 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 SillaJen 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 * 1.7184 | + | 0.528 * 0.8825 | + | 0.404 * 0.4927 | + | 0.892 * 0.9967 | + | 0.115 * 0.9262 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.85 | + | 4.679 * -0.058353 | - | 0.327 * 0.4598 |
| = | -2.34 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩814 Mil.
Revenue was 1526.632 + 1290.884 + 806.943 + 302.195 = ₩3,927 Mil.
Gross Profit was -1672.736 + 1290.884 + -394.835 + 136.531 = ₩-640 Mil.
Total Current Assets was ₩126,119 Mil.
Total Assets was ₩149,016 Mil.
Property, Plant and Equipment(Net PPE) was ₩1,739 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩939 Mil.
Selling, General, & Admin. Expense(SGA) was ₩11,742 Mil.
Total Current Liabilities was ₩16,600 Mil.
Long-Term Debt & Capital Lease Obligation was ₩566 Mil.
Net Income was -6888.103 + -7867.413 + -6707.53 + -5062.7 = ₩-26,526 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -1862.234 + -5075.85 + -5733.024 + -5159.177 = ₩-17,830 Mil.
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Total Receivables was ₩475 Mil.
Revenue was -1170.314 + 1718.423 + 2595.103 + 796.347 = ₩3,940 Mil.
Gross Profit was -3653.129 + 1718.423 + 1163.597 + 204.319 = ₩-567 Mil.
Total Current Assets was ₩52,228 Mil.
Total Assets was ₩76,715 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,381 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,146 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,368 Mil.
Total Current Liabilities was ₩10,243 Mil.
Long-Term Debt & Capital Lease Obligation was ₩8,976 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) |
| = | (813.904 / 3926.654) | / | (475.194 / 3939.559) |
| = | 0.207277 | / | 0.120621 |
| | = | 1.7184 |
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) |
| = | (-566.79 / 3939.559) | / | (-640.156 / 3926.654) |
| = | -0.143871 | / | -0.163028 |
| | = | 0.8825 |
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 - (126119.217 + 1738.635) / 149015.779) | / | (1 - (52227.813 + 2381.33) / 76714.902) |
| = | 0.141984 | / | 0.288155 |
| | = | 0.4927 |
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 |
| = | 3926.654 | / | 3939.559 |
| | = | 0.9967 |
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)) |
| = | (1145.775 / (1145.775 + 2381.33)) | / | (939.246 / (939.246 + 1738.635)) |
| = | 0.324849 | / | 0.350742 |
| | = | 0.9262 |
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) |
| = | (11741.829 / 3926.654) | / | (6367.683 / 3939.559) |
| = | 2.990289 | / | 1.616344 |
| | = | 1.85 |
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) |
| = | ((565.906 + 16600.096) / 149015.779) | / | ((8976.23 + 10242.618) / 76714.902) |
| = | 0.115196 | / | 0.250523 |
| | = | 0.4598 |
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 |
| = | (-26525.746 - 0 | - | -17830.285) | / | 149015.779 |
| | = | -0.058353 |
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.
SillaJen has a M-score of -2.34 suggests that the company is unlikely to be a manipulator.
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