PSK Beneish M-Score Historical Data
The historical data trend for PSK'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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PSK Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
|
-1.93 |
-2.73 |
-2.41 |
-2.20 |
-2.56 |
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PSK Quarterly Data
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Dec18 |
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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-2.20 |
-2.29 |
-2.86 |
-2.75 |
-2.56 |
Competitive Comparison
For the Semiconductor Equipment & Materials subindustry, PSK'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.
PSK Beneish M-Score Distribution
For the Semiconductors industry and Technology sector, PSK's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where PSK's Beneish M-Score falls into.
PSK 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 PSK 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 * 0.8148 | + | 0.528 * 0.9895 | + | 0.404 * 1.6921 | + | 0.892 * 0.7634 | + | 0.115 * 1.3196 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4791 | + | 4.679 * 0.004528 | - | 0.327 * 0.8366 |
| = | -2.56 |
* 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 ₩34,044 Mil.
Revenue was 108664.931 + 93981.378 + 65537.411 + 83680.085 = ₩351,864 Mil.
Gross Profit was 52072.07 + 50565.122 + 27121.67 + 34841.944 = ₩164,601 Mil.
Total Current Assets was ₩353,609 Mil.
Total Assets was ₩494,393 Mil.
Property, Plant and Equipment(Net PPE) was ₩73,238 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩6,152 Mil.
Selling, General, & Admin. Expense(SGA) was ₩30,228 Mil.
Total Current Liabilities was ₩86,122 Mil.
Long-Term Debt & Capital Lease Obligation was ₩13,572 Mil.
Net Income was 18976.323 + 19974.059 + 2531.678 + 11038.128 = ₩52,520 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 14364.535 + -1171.798 + 11625.258 + 25463.475 = ₩50,281 Mil.
|
Total Receivables was ₩54,732 Mil.
Revenue was 90886.18 + 142066.262 + 133909.105 + 94047.655 = ₩460,909 Mil.
Gross Profit was 33698.405 + 76641.026 + 57523.14 + 45488.59 = ₩213,351 Mil.
Total Current Assets was ₩383,951 Mil.
Total Assets was ₩472,649 Mil.
Property, Plant and Equipment(Net PPE) was ₩50,537 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,756 Mil.
Selling, General, & Admin. Expense(SGA) was ₩26,771 Mil.
Total Current Liabilities was ₩100,918 Mil.
Long-Term Debt & Capital Lease Obligation was ₩13,005 Mil.
|
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) |
| = | (34043.866 / 351863.805) | / | (54732.142 / 460909.202) |
| = | 0.096753 | / | 0.118748 |
| | = | 0.8148 |
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) |
| = | (213351.161 / 460909.202) | / | (164600.806 / 351863.805) |
| = | 0.462892 | / | 0.467797 |
| | = | 0.9895 |
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 - (353608.679 + 73238.471) / 494393.356) | / | (1 - (383950.967 + 50536.627) / 472649.34) |
| = | 0.136624 | / | 0.08074 |
| | = | 1.6921 |
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 |
| = | 351863.805 | / | 460909.202 |
| | = | 0.7634 |
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)) |
| = | (5755.882 / (5755.882 + 50536.627)) | / | (6151.523 / (6151.523 + 73238.471)) |
| = | 0.10225 | / | 0.077485 |
| | = | 1.3196 |
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) |
| = | (30228.335 / 351863.805) | / | (26770.595 / 460909.202) |
| = | 0.085909 | / | 0.058082 |
| | = | 1.4791 |
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) |
| = | ((13572.242 + 86122.494) / 494393.356) | / | ((13004.51 + 100917.651) / 472649.34) |
| = | 0.201651 | / | 0.241029 |
| | = | 0.8366 |
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 |
| = | (52520.188 - 0 | - | 50281.47) | / | 494393.356 |
| | = | 0.004528 |
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.
PSK has a M-score of -2.56 suggests that the company is unlikely to be a manipulator.
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