TE Connectivity Beneish M-Score Historical Data
The historical data trend for TE Connectivity'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.
TE Connectivity Beneish M-Score Chart
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TE Connectivity Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.52 |
-2.71 |
-2.35 |
-2.46 |
-2.62 |
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TE Connectivity 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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-2.44 |
-2.50 |
-2.58 |
-2.62 |
-2.40 |
Competitive Comparison of TE Connectivity's Beneish M-Score
For the Electronic Components subindustry, TE Connectivity'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.
TE Connectivity's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, TE Connectivity's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where TE Connectivity's Beneish M-Score falls into.
TE Connectivity 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 TE Connectivity 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 * 0.9868 | + | 0.528 * 0.9839 | + | 0.404 * 1.0629 | + | 0.892 * 0.9567 | + | 0.115 * 0.9844 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0747 | + | 4.679 * 0.014224 | - | 0.327 * 0.8993 |
| = | -2.43 |
* 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 €2,593 Mil.
Revenue was 3513.027 + 3780.795 + 3690.154 + 3885.44 = €14,869 Mil.
Gross Profit was 1214.108 + 1204.045 + 1198.977 + 1199.256 = €4,816 Mil.
Total Current Assets was €6,823 Mil.
Total Assets was €21,156 Mil.
Property, Plant and Equipment(Net PPE) was €3,534 Mil.
Depreciation, Depletion and Amortization(DDA) was €743 Mil.
Selling, General, & Admin. Expense(SGA) was €1,579 Mil.
Total Current Liabilities was €3,678 Mil.
Long-Term Debt & Capital Lease Obligation was €3,287 Mil.
Net Income was 1653.351 + 517.224 + 487.344 + 404.422 = €3,062 Mil.
Non Operating Income was -29.344 + -62.779 + -60.918 + -122.354 = €-275 Mil.
Cash Flow from Operations was 659.323 + 1066.306 + 719.017 + 592.156 = €3,037 Mil.
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Total Receivables was €2,747 Mil.
Revenue was 3625.904 + 4402.59 + 3875.762 + 3638.356 = €15,543 Mil.
Gross Profit was 1120.528 + 1362.49 + 1256.288 + 1213.996 = €4,953 Mil.
Total Current Assets was €6,908 Mil.
Total Assets was €20,157 Mil.
Property, Plant and Equipment(Net PPE) was €3,569 Mil.
Depreciation, Depletion and Amortization(DDA) was €736 Mil.
Selling, General, & Admin. Expense(SGA) was €1,536 Mil.
Total Current Liabilities was €4,172 Mil.
Long-Term Debt & Capital Lease Obligation was €3,208 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) |
| = | (2593.276 / 14869.416) | / | (2747.04 / 15542.612) |
| = | 0.174403 | / | 0.176742 |
| | = | 0.9868 |
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) |
| = | (4953.302 / 15542.612) | / | (4816.386 / 14869.416) |
| = | 0.318692 | / | 0.323912 |
| | = | 0.9839 |
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 - (6823.397 + 3534.118) / 21156.107) | / | (1 - (6908.192 + 3569.264) / 20157.232) |
| = | 0.510424 | / | 0.480214 |
| | = | 1.0629 |
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 |
| = | 14869.416 | / | 15542.612 |
| | = | 0.9567 |
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)) |
| = | (736.49 / (736.49 + 3569.264)) | / | (743.236 / (743.236 + 3534.118)) |
| = | 0.171048 | / | 0.173761 |
| | = | 0.9844 |
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) |
| = | (1578.955 / 14869.416) | / | (1535.674 / 15542.612) |
| = | 0.106188 | / | 0.098804 |
| | = | 1.0747 |
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) |
| = | ((3287.445 + 3678.087) / 21156.107) | / | ((3207.712 + 4172.48) / 20157.232) |
| = | 0.329245 | / | 0.366131 |
| | = | 0.8993 |
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 |
| = | (3062.341 - -275.395 | - | 3036.802) | / | 21156.107 |
| | = | 0.014224 |
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.
TE Connectivity has a M-score of -2.43 suggests that the company is unlikely to be a manipulator.
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