3Peakorporated Beneish M-Score Historical Data
The historical data trend for 3Peakorporated'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.
3Peakorporated Beneish M-Score Chart
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3Peakorporated Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
-2.61 |
1.76 |
-2.38 |
-2.07 |
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3Peakorporated Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
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Dec21 |
Mar22 |
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Dec22 |
Mar23 |
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Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.15 |
-2.95 |
-2.79 |
-2.07 |
-2.78 |
Competitive Comparison of 3Peakorporated's Beneish M-Score
For the Semiconductor Equipment & Materials subindustry, 3Peakorporated'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.
3Peakorporated's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, 3Peakorporated's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where 3Peakorporated's Beneish M-Score falls into.
3Peakorporated 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 3Peakorporated 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 * 1.0801 | + | 0.528 * 1.2009 | + | 0.404 * 0.7387 | + | 0.892 * 0.5984 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3506 | + | 4.679 * -0.00548 | - | 0.327 * 0.7929 |
| = | -2.78 |
* 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 ¥151.5 Mil.
Revenue was 200.012 + 280.325 + 201.185 + 304.75 = ¥986.3 Mil.
Gross Profit was 95.275 + 130.66 + 100.634 + 157.281 = ¥483.9 Mil.
Total Current Assets was ¥4,952.1 Mil.
Total Assets was ¥5,806.4 Mil.
Property, Plant and Equipment(Net PPE) was ¥393.9 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0.0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥107.4 Mil.
Total Current Liabilities was ¥266.1 Mil.
Long-Term Debt & Capital Lease Obligation was ¥31.4 Mil.
Net Income was -49.168 + -51.017 + 2.217 + 12.448 = ¥-85.5 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ¥0.0 Mil.
Cash Flow from Operations was 12.175 + -21.815 + -50.976 + 6.912 = ¥-53.7 Mil.
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Total Receivables was ¥234.4 Mil.
Revenue was 307.259 + 314.723 + 470.561 + 555.661 = ¥1,648.2 Mil.
Gross Profit was 177.758 + 185.984 + 277.17 + 330.105 = ¥971.0 Mil.
Total Current Assets was ¥3,469.8 Mil.
Total Assets was ¥4,086.3 Mil.
Property, Plant and Equipment(Net PPE) was ¥177.8 Mil.
Depreciation, Depletion and Amortization(DDA) was ¥0.0 Mil.
Selling, General, & Admin. Expense(SGA) was ¥132.9 Mil.
Total Current Liabilities was ¥232.4 Mil.
Long-Term Debt & Capital Lease Obligation was ¥31.6 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) |
| = | (151.509 / 986.272) | / | (234.407 / 1648.204) |
| = | 0.153618 | / | 0.14222 |
| | = | 1.0801 |
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) |
| = | (971.017 / 1648.204) | / | (483.85 / 986.272) |
| = | 0.589136 | / | 0.490585 |
| | = | 1.2009 |
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 - (4952.053 + 393.91) / 5806.352) | / | (1 - (3469.798 + 177.848) / 4086.286) |
| = | 0.079291 | / | 0.107344 |
| | = | 0.7387 |
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 |
| = | 986.272 | / | 1648.204 |
| | = | 0.5984 |
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)) |
| = | (0 / (0 + 177.848)) | / | (0 / (0 + 393.91)) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (107.381 / 986.272) | / | (132.867 / 1648.204) |
| = | 0.108876 | / | 0.080613 |
| | = | 1.3506 |
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) |
| = | ((31.429 + 266.089) / 5806.352) | / | ((31.637 + 232.447) / 4086.286) |
| = | 0.05124 | / | 0.064627 |
| | = | 0.7929 |
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 |
| = | (-85.52 - 0 | - | -53.704) | / | 5806.352 |
| | = | -0.00548 |
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.
3Peakorporated has a M-score of -2.78 suggests that the company is unlikely to be a manipulator.
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