Compare Return On Equity 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 Return On Equity Analysis
Compare General Motors, and UNH 515 15 Return On Equity Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GM | 0.3617 | 0.2411 | 0.1707 | 0.1255 | 0.1114 | 0.243 | 0.2151 | (0.1104) | 0.2062 | 0.1611 | 0.1427 | 0.1677 | 0.1465 | 0.1575 | 0.15 |
General Motors, and UNH 515 15 Return On Equity description
Return on Equity is the amount of entities net income returned as a percentage of companies equity. Return on equity measures companies profitability by revealing how much profit organizations generates with the money shareholders have invested. A measure of the profitability of a business in relation to the equity, calculated by dividing net income by shareholder's equity.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. | FinTech Invested over 40 shares | |
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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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