KLA Beneish M-Score Historical Data
The historical data trend for KLA'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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KLA Annual Data
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Trend |
Jun14 |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-0.99 |
-2.52 |
-2.40 |
-2.27 |
-2.58 |
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KLA Quarterly Data
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Mar19 |
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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-2.27 |
-2.45 |
-2.58 |
-2.73 |
-2.88 |
Competitive Comparison
For the Semiconductor Equipment & Materials subindustry, KLA'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.
KLA Beneish M-Score Distribution
For the Semiconductors industry and Technology sector, KLA's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where KLA's Beneish M-Score falls into.
KLA 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 KLA 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 * 0.8774 | + | 0.528 * 1.0157 | + | 0.404 * 0.899 | + | 0.892 * 0.9225 | + | 0.115 * 1.1246 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.102 | + | 4.679 * -0.040264 | - | 0.327 * 0.9805 |
| = | -2.88 |
* 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 $1,945 Mil.
Revenue was 2486.726 + 2396.956 + 2355.137 + 2432.608 = $9,671 Mil.
Gross Profit was 1509.98 + 1450.065 + 1392.188 + 1427.262 = $5,779 Mil.
Total Current Assets was $8,749 Mil.
Total Assets was $14,281 Mil.
Property, Plant and Equipment(Net PPE) was $1,324 Mil.
Depreciation, Depletion and Amortization(DDA) was $411 Mil.
Selling, General, & Admin. Expense(SGA) was $966 Mil.
Total Current Liabilities was $4,571 Mil.
Long-Term Debt & Capital Lease Obligation was $5,299 Mil.
Net Income was 582.534 + 741.375 + 684.654 + 697.837 = $2,706 Mil.
Non Operating Income was -186.846 + 26.739 + -49.319 + 14.864 = $-195 Mil.
Cash Flow from Operations was 622.242 + 883.74 + 959.115 + 1010.855 = $3,476 Mil.
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Total Receivables was $2,403 Mil.
Revenue was 2983.887 + 2724.424 + 2486.739 + 2288.676 = $10,484 Mil.
Gross Profit was 1775.101 + 1683.198 + 1508.175 + 1396.585 = $6,363 Mil.
Total Current Assets was $8,133 Mil.
Total Assets was $13,729 Mil.
Property, Plant and Equipment(Net PPE) was $1,097 Mil.
Depreciation, Depletion and Amortization(DDA) was $398 Mil.
Selling, General, & Admin. Expense(SGA) was $950 Mil.
Total Current Liabilities was $3,483 Mil.
Long-Term Debt & Capital Lease Obligation was $6,195 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) |
| = | (1944.822 / 9671.427) | / | (2402.659 / 10483.726) |
| = | 0.201089 | / | 0.22918 |
| | = | 0.8774 |
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) |
| = | (6363.059 / 10483.726) | / | (5779.495 / 9671.427) |
| = | 0.606946 | / | 0.597585 |
| | = | 1.0157 |
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 - (8748.721 + 1323.925) / 14280.501) | / | (1 - (8132.582 + 1096.733) / 13729.074) |
| = | 0.294657 | / | 0.327754 |
| | = | 0.899 |
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 |
| = | 9671.427 | / | 10483.726 |
| | = | 0.9225 |
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)) |
| = | (398.421 / (398.421 + 1096.733)) | / | (411.133 / (411.133 + 1323.925)) |
| = | 0.266475 | / | 0.236956 |
| | = | 1.1246 |
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) |
| = | (966.139 / 9671.427) | / | (950.343 / 10483.726) |
| = | 0.099896 | / | 0.090649 |
| | = | 1.102 |
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) |
| = | ((5298.924 + 4570.997) / 14280.501) | / | ((6194.765 + 3482.501) / 13729.074) |
| = | 0.691147 | / | 0.704874 |
| | = | 0.9805 |
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 |
| = | (2706.4 - -194.562 | - | 3475.952) | / | 14280.501 |
| | = | -0.040264 |
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.
KLA has a M-score of -2.88 suggests that the company is unlikely to be a manipulator.
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