Wolfspeed Beneish M-Score Historical Data
The historical data trend for Wolfspeed'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.
Wolfspeed Beneish M-Score Chart
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Wolfspeed Annual Data
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Trend |
Jun14 |
Jun15 |
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Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-2.27 |
-2.89 |
-2.48 |
-1.38 |
-2.98 |
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Wolfspeed Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
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Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.97 |
-2.74 |
-2.98 |
-2.79 |
-2.24 |
Competitive Comparison of Wolfspeed's Beneish M-Score
For the Semiconductors subindustry, Wolfspeed'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.
Wolfspeed's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Wolfspeed's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Wolfspeed's Beneish M-Score falls into.
Wolfspeed 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 Wolfspeed 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 * 0.9236 | + | 0.528 * 1.611 | + | 0.404 * 1.1962 | + | 0.892 * 1.1162 | + | 0.115 * 1.2028 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0981 | + | 4.679 * -0.026172 | - | 0.327 * 1.2279 |
| = | -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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $303.8 Mil.
Revenue was 208.4 + 197.4 + 235.8 + 228.7 = $870.3 Mil.
Gross Profit was 27.8 + 24.7 + 64.6 + 68.1 = $185.2 Mil.
Total Current Assets was $3,446.1 Mil.
Total Assets was $7,290.2 Mil.
Property, Plant and Equipment(Net PPE) was $2,850.1 Mil.
Depreciation, Depletion and Amortization(DDA) was $184.7 Mil.
Selling, General, & Admin. Expense(SGA) was $253.6 Mil.
Total Current Liabilities was $671.2 Mil.
Long-Term Debt & Capital Lease Obligation was $5,176.6 Mil.
Net Income was -144.7 + -395.7 + -113.3 + -99.5 = $-753.2 Mil.
Non Operating Income was -17.1 + -18.5 + -58 + -56 = $-149.6 Mil.
Cash Flow from Operations was -202.5 + -147.4 + -51.9 + -11 = $-412.8 Mil.
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Total Receivables was $294.7 Mil.
Revenue was 173.8 + 189.4 + 228.5 + 188 = $779.7 Mil.
Gross Profit was 56.7 + 67.7 + 78.9 + 64 = $267.3 Mil.
Total Current Assets was $3,084.3 Mil.
Total Assets was $5,342.9 Mil.
Property, Plant and Equipment(Net PPE) was $1,649.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $130.3 Mil.
Selling, General, & Admin. Expense(SGA) was $206.9 Mil.
Total Current Liabilities was $460.0 Mil.
Long-Term Debt & Capital Lease Obligation was $3,030.4 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) |
| = | (303.8 / 870.3) | / | (294.7 / 779.7) |
| = | 0.349075 | / | 0.377966 |
| | = | 0.9236 |
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) |
| = | (267.3 / 779.7) | / | (185.2 / 870.3) |
| = | 0.342824 | / | 0.2128 |
| | = | 1.611 |
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 - (3446.1 + 2850.1) / 7290.2) | / | (1 - (3084.3 + 1649.6) / 5342.9) |
| = | 0.136347 | / | 0.113983 |
| | = | 1.1962 |
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 |
| = | 870.3 | / | 779.7 |
| | = | 1.1162 |
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)) |
| = | (130.3 / (130.3 + 1649.6)) | / | (184.7 / (184.7 + 2850.1)) |
| = | 0.073206 | / | 0.060861 |
| | = | 1.2028 |
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) |
| = | (253.6 / 870.3) | / | (206.9 / 779.7) |
| = | 0.291394 | / | 0.265358 |
| | = | 1.0981 |
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) |
| = | ((5176.6 + 671.2) / 7290.2) | / | ((3030.4 + 460) / 5342.9) |
| = | 0.802145 | / | 0.653278 |
| | = | 1.2279 |
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 |
| = | (-753.2 - -149.6 | - | -412.8) | / | 7290.2 |
| | = | -0.026172 |
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.
Wolfspeed has a M-score of -2.24 suggests that the company is unlikely to be a manipulator.
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