Compare Shareholders Equity Per Share 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.
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Cross Equities Shareholders Equity Per Share Analysis
Compare US49326EEL39, and Valmont Industries Shareholders Equity Per Share Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| VMI | 7.0396 | 45.4978 | 66.7011 | 66.7011 | 66.7011 | 66.7011 | 43.5505 | 66.7011 | 66.7011 | 66.7011 | 66.7011 | 64.6249 | 77.0359 | 77.0359 | 69.33 | 72.8 |
US49326EEL39, and Valmont Industries Shareholders Equity Per Share 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. | Blockchain Invested few shares | |
 | Business Services Invested few shares | |
 | Banking Invested over 30 shares | |
 | Chemicals Invested over 30 shares | |
 | Driverless Cars Invested over 60 shares | |
 | Hedge Favorites Invested few shares | |
 | Automobiles and Trucks Invested over 300 shares | |
 | Macroaxis Index Invested over 500 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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