Intel Beneish M-Score Historical Data
The historical data trend for Intel'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.
Intel Beneish M-Score Chart
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Intel Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-3.12 |
-2.42 |
-3.31 |
-2.80 |
-2.92 |
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Intel 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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-2.80 |
-2.79 |
-2.69 |
-2.91 |
-2.92 |
Competitive Comparison of Intel's Beneish M-Score
For the Semiconductors subindustry, Intel'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.
Intel's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, Intel's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Intel's Beneish M-Score falls into.
Intel 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 Intel 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 * 1.044 | + | 0.528 * 1.2257 | + | 0.404 * 0.7784 | + | 0.892 * 0.9792 | + | 0.115 * 0.9475 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9982 | + | 4.679 * -0.099555 | - | 0.327 * 1.0649 |
| = | -2.92 |
* 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 лв6,227 Mil.
Revenue was 25530.305 + 23782.93 + 22975.485 + 22780.337 = лв95,069 Mil.
Gross Profit was 9997.281 + 3575.317 + 8140.694 + 9340.225 = лв31,054 Mil.
Total Current Assets was лв84,726 Mil.
Total Assets was лв351,776 Mil.
Property, Plant and Equipment(Net PPE) was лв193,212 Mil.
Depreciation, Depletion and Amortization(DDA) was лв20,372 Mil.
Selling, General, & Admin. Expense(SGA) was лв9,859 Mil.
Total Current Liabilities was лв63,854 Mil.
Long-Term Debt & Capital Lease Obligation was лв82,861 Mil.
Net Income was -225.583 + -29789.534 + -2882.454 + -682.121 = лв-33,580 Mil.
Non Operating Income was -888.011 + -10349.979 + -1903.136 + -256.019 = лв-13,397 Mil.
Cash Flow from Operations was 5666.439 + 7258.055 + 4103.468 + -2189.591 = лв14,838 Mil.
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Total Receivables was лв6,091 Mil.
Revenue was 27582.04 + 25347.69 + 23183.164 + 20973.88 = лв97,087 Mil.
Gross Profit was 12616.554 + 10774.29 + 8303.615 + 7175.699 = лв38,870 Mil.
Total Current Assets was лв77,466 Mil.
Total Assets was лв342,980 Mil.
Property, Plant and Equipment(Net PPE) was лв173,031 Mil.
Depreciation, Depletion and Amortization(DDA) was лв17,191 Mil.
Selling, General, & Admin. Expense(SGA) was лв10,087 Mil.
Total Current Liabilities was лв50,225 Mil.
Long-Term Debt & Capital Lease Obligation was лв84,107 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) |
| = | (6226.816 / 95069.057) | / | (6090.75 / 97086.774) |
| = | 0.065498 | / | 0.062735 |
| | = | 1.044 |
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) |
| = | (38870.158 / 97086.774) | / | (31053.517 / 95069.057) |
| = | 0.400365 | / | 0.326642 |
| | = | 1.2257 |
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 - (84726.239 + 193212.134) / 351775.741) | / | (1 - (77466.395 + 173031.377) / 342979.781) |
| = | 0.209899 | / | 0.269643 |
| | = | 0.7784 |
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 |
| = | 95069.057 | / | 97086.774 |
| | = | 0.9792 |
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)) |
| = | (17190.883 / (17190.883 + 173031.377)) | / | (20372.326 / (20372.326 + 193212.134)) |
| = | 0.090373 | / | 0.095383 |
| | = | 0.9475 |
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) |
| = | (9859.424 / 95069.057) | / | (10086.798 / 97086.774) |
| = | 0.103708 | / | 0.103895 |
| | = | 0.9982 |
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) |
| = | ((82860.701 + 63854.409) / 351775.741) | / | ((84106.78 + 50224.52) / 342979.781) |
| = | 0.41707 | / | 0.39166 |
| | = | 1.0649 |
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 |
| = | (-33579.692 - -13397.145 | - | 14838.371) | / | 351775.741 |
| | = | -0.099555 |
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.
Intel has a M-score of -2.92 suggests that the company is unlikely to be a manipulator.
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