Peptron Beneish M-Score Historical Data
The historical data trend for Peptron'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.
Peptron Beneish M-Score Chart
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Peptron Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-0.20 |
-1.97 |
-1.80 |
0.53 |
-2.90 |
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Peptron Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.84 |
-2.41 |
-3.05 |
-2.90 |
-3.24 |
Competitive Comparison of Peptron's Beneish M-Score
For the Biotechnology subindustry, Peptron'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.
Peptron's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, Peptron's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Peptron's Beneish M-Score falls into.
Peptron 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 Peptron 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 * 1.1096 | + | 0.528 * 0.9344 | + | 0.404 * 1.4287 | + | 0.892 * 0.6332 | + | 0.115 * 1.6378 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.5102 | + | 4.679 * -0.102128 | - | 0.327 * 1.5503 |
| = | -3.24 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩2,529 Mil.
Revenue was 477.267 + 799.672 + 683.466 + 695.353 = ₩2,656 Mil.
Gross Profit was 76.195 + 379.629 + 234.202 + 238.855 = ₩929 Mil.
Total Current Assets was ₩5,980 Mil.
Total Assets was ₩49,909 Mil.
Property, Plant and Equipment(Net PPE) was ₩38,399 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,785 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,708 Mil.
Total Current Liabilities was ₩8,166 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,520 Mil.
Net Income was -4030.646 + -3261.833 + -4140.301 + -4508.114 = ₩-15,941 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -2902.611 + -1359.852 + -3189.134 + -3392.135 = ₩-10,844 Mil.
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Total Receivables was ₩3,599 Mil.
Revenue was 1163.402 + 793.234 + 1227.516 + 1009.873 = ₩4,194 Mil.
Gross Profit was 287.893 + 328.268 + 370.722 + 383.788 = ₩1,371 Mil.
Total Current Assets was ₩18,988 Mil.
Total Assets was ₩63,929 Mil.
Property, Plant and Equipment(Net PPE) was ₩39,983 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩4,980 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,832 Mil.
Total Current Liabilities was ₩10,422 Mil.
Long-Term Debt & Capital Lease Obligation was ₩59 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) |
| = | (2528.732 / 2655.758) | / | (3599.05 / 4194.025) |
| = | 0.95217 | / | 0.858137 |
| | = | 1.1096 |
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) |
| = | (1370.671 / 4194.025) | / | (928.881 / 2655.758) |
| = | 0.326815 | / | 0.349761 |
| | = | 0.9344 |
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 - (5980.159 + 38399.354) / 49909.457) | / | (1 - (18988.277 + 39982.972) / 63929.291) |
| = | 0.1108 | / | 0.077555 |
| | = | 1.4287 |
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 |
| = | 2655.758 | / | 4194.025 |
| | = | 0.6332 |
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)) |
| = | (4979.8 / (4979.8 + 39982.972)) | / | (2784.982 / (2784.982 + 38399.354)) |
| = | 0.110754 | / | 0.067622 |
| | = | 1.6378 |
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) |
| = | (2708.286 / 2655.758) | / | (2832.032 / 4194.025) |
| = | 1.019779 | / | 0.675254 |
| | = | 1.5102 |
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) |
| = | ((4519.571 + 8165.812) / 49909.457) | / | ((58.907 + 10422.209) / 63929.291) |
| = | 0.254168 | / | 0.163949 |
| | = | 1.5503 |
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 |
| = | (-15940.894 - 0 | - | -10843.732) | / | 49909.457 |
| | = | -0.102128 |
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.
Peptron has a M-score of -3.24 suggests that the company is unlikely to be a manipulator.
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