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.
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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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|
|
|
|
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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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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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|
|
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|
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-2.46 |
-2.44 |
-2.50 |
-2.58 |
-2.62 |
Competitive Comparison
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 Beneish M-Score Distribution
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 * 1.0516 | + | 0.528 * 1.0216 | + | 0.404 * 0.9686 | + | 0.892 * 0.9848 | + | 0.115 * 1.0332 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0705 | + | 4.679 * -0.038366 | - | 0.327 * 0.9654 |
| = | -2.62 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was $2,967 Mil.
Revenue was 4035 + 3998 + 4160 + 3841 = $16,034 Mil.
Gross Profit was 1285 + 1299 + 1284 + 1187 = $5,055 Mil.
Total Current Assets was $7,892 Mil.
Total Assets was $21,712 Mil.
Property, Plant and Equipment(Net PPE) was $3,754 Mil.
Depreciation, Depletion and Amortization(DDA) was $794 Mil.
Selling, General, & Admin. Expense(SGA) was $1,670 Mil.
Total Current Liabilities was $4,463 Mil.
Long-Term Debt & Capital Lease Obligation was $3,529 Mil.
Net Income was 552 + 528 + 433 + 397 = $1,910 Mil.
Non Operating Income was -67 + -66 + -131 + -125 = $-389 Mil.
Cash Flow from Operations was 1138 + 779 + 634 + 581 = $3,132 Mil.
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Total Receivables was $2,865 Mil.
Revenue was 4359 + 4097 + 4007 + 3818 = $16,281 Mil.
Gross Profit was 1349 + 1328 + 1337 + 1230 = $5,244 Mil.
Total Current Assets was $7,268 Mil.
Total Assets was $20,782 Mil.
Property, Plant and Equipment(Net PPE) was $3,567 Mil.
Depreciation, Depletion and Amortization(DDA) was $785 Mil.
Selling, General, & Admin. Expense(SGA) was $1,584 Mil.
Total Current Liabilities was $4,632 Mil.
Long-Term Debt & Capital Lease Obligation was $3,292 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) |
| = | (2967 / 16034) | / | (2865 / 16281) |
| = | 0.185044 | / | 0.175972 |
| | = | 1.0516 |
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) |
| = | (5244 / 16281) | / | (5055 / 16034) |
| = | 0.322093 | / | 0.315268 |
| | = | 1.0216 |
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 - (7892 + 3754) / 21712) | / | (1 - (7268 + 3567) / 20782) |
| = | 0.463615 | / | 0.478635 |
| | = | 0.9686 |
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 |
| = | 16034 | / | 16281 |
| | = | 0.9848 |
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)) |
| = | (785 / (785 + 3567)) | / | (794 / (794 + 3754)) |
| = | 0.180377 | / | 0.174582 |
| | = | 1.0332 |
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) |
| = | (1670 / 16034) | / | (1584 / 16281) |
| = | 0.104154 | / | 0.097291 |
| | = | 1.0705 |
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) |
| = | ((3529 + 4463) / 21712) | / | ((3292 + 4632) / 20782) |
| = | 0.368091 | / | 0.381292 |
| | = | 0.9654 |
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 |
| = | (1910 - -389 | - | 3132) | / | 21712 |
| | = | -0.038366 |
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 -2.62 suggests that the company is unlikely to be a manipulator.
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