Compare Net Income Per E B T Across Equities
You 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 positions. Check out your portfolio center.
Cross Equities Net Income Per E B T Analysis
Select Fundamental
2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
NWS | 0.5271 | 0.8729 | 2.9249 | (0.602) | (2.625) | 0.989 | 1.2 | 1.3903 | 0.6441 | 1.0138 | 0.7333 | 0.7672 | 0.4515 | 0.4872 | 0.44 | 0.5 |
NWSA | 0.5271 | 0.8729 | 2.9249 | (0.602) | (2.625) | 0.989 | 1.2 | 1.3903 | 0.6441 | 1.0138 | 0.7333 | 0.7672 | 0.4515 | 0.4872 | 0.44 | 0.5 |
LYV | 0.9979 | 0.8591 | 1.2351 | 8.4442 | 0.9664 | (10.3395) | (0.9728) | 10.41 | (0.1346) | 0.6386 | 0.9844 | 0.9959 | 0.8096 | 0.6297 | 1.2121 | 1.27 |
PARAA | 0.6146 | 0.6265 | 0.6486 | 0.6486 | 1.3674 | 0.6985 | 0.5655 | 0.1804 | 0.8563 | 0.9889 | 0.7696 | 0.8726 | 0.872 | 0.4852 | 0.44 | 0.47 |
FWONA | 2.3474 | 1.1029 | 0.7028 | 0.9914 | 0.3861 | 0.6318 | 0.658 | (0.8388) | 0.75 | 0.7756 | 0.8414 | 0.7643 | 2.2231 | 0.8768 | 1.01 | 0.96 |
MCS | 0.5995 | 0.7719 | 0.7719 | 0.7719 | 0.7719 | 0.6102 | 0.7719 | 0.7719 | 0.7719 | 0.6833 | 0.6377 | 0.6833 | 0.6833 | 0.6377 | 0.57 | 0.66 |
MSGS | 1.2121 | 1.2121 | 1.0198 | 1.0147 | 1.0108 | 1.0039 | 0.8957 | 8.0561 | 1.762 | 1.21 | 0.178 | 0.6916 | 0.5315 | 0.5562 | 0.64 | 0.61 |
WMG | 1.1442 | 1.037 | 0.88 | 0.9362 | 1.2133 | 0.6098 | (71.5) | 0.6946 | 0.9588 | 1.0626 | 0.6667 | 0.7446 | 0.7061 | 0.7238 | 0.83 | 0.87 |
FOX | 0.5817 | 0.5817 | 0.5817 | 0.5817 | 0.5817 | 0.5817 | 0.6122 | 1.0078 | 0.7172 | 0.6824 | 0.7368 | 0.7113 | 0.7137 | 0.7134 | 0.64 | 0.58 |
PARA | 0.6146 | 0.6265 | 0.6486 | 0.6486 | 1.3674 | 0.6985 | 0.5655 | 0.1804 | 0.8563 | 0.9889 | 0.7696 | 0.8726 | 0.872 | 0.4852 | 0.44 | 0.47 |
News Corp B, News Corp A, and Live Nation Entertainment Net Income Per E B T description
Trending Themes
If you are a self-driven investor, you will appreciate our idea-generating investing themes. Our themes help you align your investments inspirations with your core values and are essential building blocks of your portfolios. A typical investing theme is an unweighted collection of up to 20 funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of equities with common characteristics such as industry and growth potential, volatility, or market segment.![]() | Artificial Intelligence Invested few shares | |
![]() | FinTech Invested over 30 shares | |
![]() | Automobiles and Trucks Invested over 60 shares | |
![]() | Banking Invested over 30 shares | |
![]() | Investor Favorites Invested few shares | |
![]() | Driverless Cars Invested over 60 shares | |
![]() | Disruptive Technologies Invested few shares | |
![]() | Momentum Invested few shares | |
![]() | Chemicals Invested over 30 shares | |
![]() | ESG Investing Invested few shares | |
![]() | Online Gaming Invested over 20 shares |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Holdings module to check your current holdings and cash postion to detemine if your portfolio needs rebalancing.
Other Complementary Tools
ETF Categories List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments | |
Portfolio Manager State of the art Portfolio Manager to monitor and improve performance of your invested capital | |
Global Correlations Find global opportunities by holding instruments from different markets | |
Commodity Directory Find actively traded commodities issued by global exchanges | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |