Compare Graham Number 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 Number Analysis
Compare Alphabet Class C, and 3X AMD Graham Number Over Time
Select Fundamental| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GOOG | 0.0708 | 8.7417 | 10.0565 | 11.8791 | 13.4858 | 15.3607 | 17.9451 | 15.0379 | 25.2123 | 28.4823 | 32.978 | 49.1359 | 45.0054 | 54.3107 | 57.03 |
Alphabet Class C, and 3X AMD Graham Number 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. | Investor Favorites Invested over 40 shares | |
 | Hedge Favorites Invested over 50 shares | |
 | Dividend Beast Invested over 50 shares | |
 | Business Services Invested few shares | |
 | Cash Cows Invested few shares | |
 | Impulse Invested few shares | |
 | Macroaxis Index Invested few shares | |
 | Investing Invested few shares | |
 | Semiconductor Invested few 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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