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 |
Sep12 |
Sep13 |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
| Beneish M-Score |
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-2.58 |
-2.29 |
-2.52 |
-2.71 |
-2.35 |
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TE Connectivity Quarterly Data
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Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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-2.34 |
-2.35 |
-2.41 |
-2.37 |
-2.37 |
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 * 0.9577 | + | 0.528 * 0.9756 | + | 0.404 * 0.9975 | + | 0.892 * 1.0956 | + | 0.115 * 0.9922 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9596 | + | 4.679 * 0.0163 | - | 0.327 * 1.0039 |
| = | -2.37 |
* 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 (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $3,132 Mil.
Revenue was 4097 + 4007 + 3818 + 3818 = $15,740 Mil.
Gross Profit was 1328 + 1337 + 1230 + 1263 = $5,158 Mil.
Total Current Assets was $7,583 Mil.
Total Assets was $21,348 Mil.
Property, Plant and Equipment(Net PPE) was $3,712 Mil.
Depreciation, Depletion and Amortization(DDA) was $776 Mil.
Selling, General, & Admin. Expense(SGA) was $1,556 Mil.
Total Current Liabilities was $5,058 Mil.
Long-Term Debt & Capital Lease Obligation was $3,380 Mil.
Net Income was 594 + 560 + 566 + 794 = $2,514 Mil.
Non Operating Income was -33 + -26 + -5 + -68 = $-132 Mil.
Cash Flow from Operations was 579 + 413 + 532 + 774 = $2,298 Mil.
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Total Receivables was $2,985 Mil.
Revenue was 3845 + 3738 + 3522 + 3261 = $14,366 Mil.
Gross Profit was 1268 + 1210 + 1146 + 969 = $4,593 Mil.
Total Current Assets was $7,394 Mil.
Total Assets was $21,058 Mil.
Property, Plant and Equipment(Net PPE) was $3,723 Mil.
Depreciation, Depletion and Amortization(DDA) was $771 Mil.
Selling, General, & Admin. Expense(SGA) was $1,480 Mil.
Total Current Liabilities was $4,662 Mil.
Long-Term Debt & Capital Lease Obligation was $3,629 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) |
| = | (3132 / 15740) | / | (2985 / 14366) |
| = | 0.19898348 | / | 0.20778226 |
| | = | 0.9577 |
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) |
| = | (4593 / 14366) | / | (5158 / 15740) |
| = | 0.31971321 | / | 0.32770013 |
| | = | 0.9756 |
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 - (7583 + 3712) / 21348) | / | (1 - (7394 + 3723) / 21058) |
| = | 0.47091062 | / | 0.47207712 |
| | = | 0.9975 |
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 |
| = | 15740 | / | 14366 |
| | = | 1.0956 |
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)) |
| = | (771 / (771 + 3723)) | / | (776 / (776 + 3712)) |
| = | 0.17156208 | / | 0.17290553 |
| | = | 0.9922 |
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) |
| = | (1556 / 15740) | / | (1480 / 14366) |
| = | 0.09885642 | / | 0.10302102 |
| | = | 0.9596 |
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) |
| = | ((3380 + 5058) / 21348) | / | ((3629 + 4662) / 21058) |
| = | 0.39525951 | / | 0.3937221 |
| | = | 1.0039 |
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 |
| = | (2514 - -132 | - | 2298) | / | 21348 |
| | = | 0.0163 |
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 -2.37 suggests that the company is unlikely to be a manipulator.
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