Compare Graham Net Net 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 Graham Net Net Analysis
Compare Alphabet Class C, and SCE Trust VI Graham Net Net Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GOOG | (0.0146) | 2.7057 | 2.4981 | 3.1818 | 3.4441 | 4.1335 | 4.9929 | 5.157 | 5.066 | 4.7883 | 4.6653 | 4.6491 | 2.7689 | 2.2071 | 2.02 |
Alphabet Class C, and SCE Trust VI Graham Net Net 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. | Macroaxis Index Invested few shares | |
 | Online Gaming Invested few shares | |
 | Tech Growth Invested one share | |
 | Power Assets Invested few shares | |
 | Disruptive Technologies Invested over 20 shares | |
 | Artificial Intelligence Invested one share | |
 | Momentum Invested few shares | |
 | Rentals Invested one share | |
 | Impulse Invested few shares | |
 | Investor Favorites Invested over 200 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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