Energy Transfer Income Tax Expense Over Time
| ET-PI Stock | 11.96 0.07 0.59% |
With this module, investors can use any or all of fundamental ratio historical patterns as a complementary method for asset selection as well as a tool for deciding entry and exit points. Many technical investors use fundamentals to limit their universe of possible portfolio assets.
Check out Energy Transfer Performance and Energy Transfer Correlation. Energy |
Cross Equities Income Tax Expense Analysis
Compare Energy Transfer LP and related stocks such as MPLX LP, Plains All American, and SPACE Income Tax Expense Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MPLX | 300 K | 100 K | 300 K | (200 K) | (100 K) | 2 M | (12 M) | 1000 K | 8 M | 380 M | 2 M | 1000 K | 8 M | 11 M | 10.4 M |
| PAA | 1.3 M | 45 M | 54 M | 99 M | 171 M | 100 M | 25 M | 44 M | 198 M | 66 M | (19 M) | 73 M | 189 M | 121 M | 127 M |
| SEIC | 2.2 M | 111.8 M | 121.5 M | 146.9 M | 170.9 M | 168.8 M | 174.7 M | 152.7 M | 108.3 M | 130 M | 121.4 M | 147.1 M | 133.8 M | 132.4 M | 87 M |
| EMBC | 68 M | 68 M | 68 M | 68 M | 68 M | 68 M | 68 M | 68 M | 68 M | 58.2 M | 80 M | 33 M | 35.3 M | (34.1 M) | (32.4 M) |
| KOD | 31 K | 31 K | 31 K | 31 K | 31 K | 31 K | 31 K | (45 K) | (9.6 M) | (638 K) | 2.7 M | (153.6 K) | 7.3 M | 8.4 M | 8.9 M |
Energy Transfer LP and related stocks such as MPLX LP, Plains All American, and SPACE Income Tax Expense description
My Equities
My Current Equities and Potential Positions
| Energy Transfer LP | ET-PI |
Specialization | Energy, Oil & Gas Midstream |
| Location | Texas; U.S.A |
| Exchange | New York Stock Exchange |
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Check out Energy Transfer Performance and Energy Transfer Correlation. You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.
Energy Transfer technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.