Belden Beneish M-Score Historical Data
The historical data trend for Belden'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.
Belden Beneish M-Score Chart
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Belden Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.46 |
-2.78 |
-2.63 |
-2.38 |
-2.71 |
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Belden 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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-2.38 |
-2.52 |
-2.51 |
-2.63 |
-2.71 |
Competitive Comparison of Belden's Beneish M-Score
For the Communication Equipment subindustry, Belden'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.
Belden's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Belden's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Belden's Beneish M-Score falls into.
Belden 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 Belden 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 * 0.9756 | + | 0.528 * 0.9247 | + | 0.404 * 1.036 | + | 0.892 * 0.9638 | + | 0.115 * 1.0502 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1395 | + | 4.679 * -0.028022 | - | 0.327 * 1.0032 |
| = | -2.71 |
* 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 $414 Mil.
Revenue was 551.243 + 626.807 + 692.245 + 641.789 = $2,512 Mil.
Gross Profit was 206.365 + 241.168 + 261.328 + 246.105 = $955 Mil.
Total Current Assets was $1,457 Mil.
Total Assets was $3,240 Mil.
Property, Plant and Equipment(Net PPE) was $541 Mil.
Depreciation, Depletion and Amortization(DDA) was $99 Mil.
Selling, General, & Admin. Expense(SGA) was $493 Mil.
Total Current Liabilities was $634 Mil.
Long-Term Debt & Capital Lease Obligation was $1,279 Mil.
Net Income was 38.467 + 72.347 + 68.753 + 63.192 = $243 Mil.
Non Operating Income was 0.401 + 12.384 + 0.646 + 0.488 = $14 Mil.
Cash Flow from Operations was 159.645 + 105.278 + 86.587 + -31.872 = $320 Mil.
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Total Receivables was $440 Mil.
Revenue was 659.072 + 670.491 + 666.551 + 610.371 = $2,606 Mil.
Gross Profit was 246.478 + 238.646 + 222.305 + 208.86 = $916 Mil.
Total Current Assets was $1,536 Mil.
Total Assets was $3,162 Mil.
Property, Plant and Equipment(Net PPE) was $455 Mil.
Depreciation, Depletion and Amortization(DDA) was $89 Mil.
Selling, General, & Admin. Expense(SGA) was $449 Mil.
Total Current Liabilities was $640 Mil.
Long-Term Debt & Capital Lease Obligation was $1,220 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) |
| = | (413.806 / 2512.084) | / | (440.102 / 2606.485) |
| = | 0.164726 | / | 0.168849 |
| | = | 0.9756 |
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) |
| = | (916.289 / 2606.485) | / | (954.966 / 2512.084) |
| = | 0.351542 | / | 0.380149 |
| | = | 0.9247 |
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 - (1456.979 + 540.755) / 3240.191) | / | (1 - (1536.207 + 455.24) / 3161.675) |
| = | 0.383452 | / | 0.370129 |
| | = | 1.036 |
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 |
| = | 2512.084 | / | 2606.485 |
| | = | 0.9638 |
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)) |
| = | (88.738 / (88.738 + 455.24)) | / | (99.446 / (99.446 + 540.755)) |
| = | 0.163128 | / | 0.155336 |
| | = | 1.0502 |
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) |
| = | (492.702 / 2512.084) | / | (448.636 / 2606.485) |
| = | 0.196133 | / | 0.172123 |
| | = | 1.1395 |
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) |
| = | ((1279.152 + 633.504) / 3240.191) | / | ((1220.426 + 639.919) / 3161.675) |
| = | 0.590291 | / | 0.588405 |
| | = | 1.0032 |
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 |
| = | (242.759 - 13.919 | - | 319.638) | / | 3240.191 |
| | = | -0.028022 |
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.
Belden has a M-score of -2.71 suggests that the company is unlikely to be a manipulator.
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