Littelfuse Beneish M-Score Historical Data
The historical data trend for Littelfuse'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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Littelfuse Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.68 |
-2.53 |
-2.31 |
-2.42 |
-2.67 |
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Littelfuse 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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|
|
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|
|
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|
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-2.42 |
-2.53 |
-2.44 |
-2.60 |
-2.67 |
Competitive Comparison
For the Electronic Components subindustry, Littelfuse'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.
Littelfuse Beneish M-Score Distribution
For the Hardware industry and Technology sector, Littelfuse's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Littelfuse's Beneish M-Score falls into.
Littelfuse 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 Littelfuse 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 * 1.0027 | + | 0.528 * 1.0512 | + | 0.404 * 1.0708 | + | 0.892 * 0.9398 | + | 0.115 * 0.9233 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0944 | + | 4.679 * -0.047307 | - | 0.327 * 0.8443 |
| = | -2.67 |
* 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 $296 Mil.
Revenue was 533.807 + 607.071 + 611.997 + 609.782 = $2,363 Mil.
Gross Profit was 193.581 + 226.871 + 234.832 + 244.957 = $900 Mil.
Total Current Assets was $1,409 Mil.
Total Assets was $3,995 Mil.
Property, Plant and Equipment(Net PPE) was $556 Mil.
Depreciation, Depletion and Amortization(DDA) was $137 Mil.
Selling, General, & Admin. Expense(SGA) was $355 Mil.
Total Current Liabilities was $375 Mil.
Long-Term Debt & Capital Lease Obligation was $907 Mil.
Net Income was 42.881 + 57.788 + 70.071 + 88.745 = $259 Mil.
Non Operating Income was 1.209 + -12.765 + -3.401 + 6.058 = $-9 Mil.
Cash Flow from Operations was 144.247 + 161.507 + 98.226 + 53.407 = $457 Mil.
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Total Receivables was $314 Mil.
Revenue was 613.251 + 658.88 + 618.436 + 623.33 = $2,514 Mil.
Gross Profit was 228.525 + 256.821 + 262.971 + 258.596 = $1,007 Mil.
Total Current Assets was $1,512 Mil.
Total Assets was $3,904 Mil.
Property, Plant and Equipment(Net PPE) was $538 Mil.
Depreciation, Depletion and Amortization(DDA) was $121 Mil.
Selling, General, & Admin. Expense(SGA) was $345 Mil.
Total Current Liabilities was $572 Mil.
Long-Term Debt & Capital Lease Obligation was $912 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) |
| = | (295.719 / 2362.657) | / | (313.793 / 2513.897) |
| = | 0.125164 | / | 0.124823 |
| | = | 1.0027 |
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) |
| = | (1006.913 / 2513.897) | / | (900.241 / 2362.657) |
| = | 0.400539 | / | 0.381029 |
| | = | 1.0512 |
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 - (1408.6 + 555.523) / 3995.275) | / | (1 - (1511.796 + 538.492) / 3903.734) |
| = | 0.508389 | / | 0.474788 |
| | = | 1.0708 |
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 |
| = | 2362.657 | / | 2513.897 |
| | = | 0.9398 |
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)) |
| = | (120.706 / (120.706 + 538.492)) | / | (137.428 / (137.428 + 555.523)) |
| = | 0.18311 | / | 0.198323 |
| | = | 0.9233 |
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) |
| = | (354.655 / 2362.657) | / | (344.813 / 2513.897) |
| = | 0.150109 | / | 0.137163 |
| | = | 1.0944 |
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) |
| = | ((907.387 + 375.494) / 3995.275) | / | ((912.284 + 572.295) / 3903.734) |
| = | 0.3211 | / | 0.380297 |
| | = | 0.8443 |
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 |
| = | (259.485 - -8.899 | - | 457.387) | / | 3995.275 |
| | = | -0.047307 |
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.
Littelfuse has a M-score of -2.67 suggests that the company is unlikely to be a manipulator.
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