Compare Earnings Yield 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 Earnings Yield Analysis
Select Fundamental
2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SYK | 0.05 | 0.07 | 0.0622 | 0.0354 | 0.0144 | 0.0411 | 0.0367 | 0.0176 | 0.0606 | 0.0265 | 0.0174 | 0.0198 | 0.0255 | 0.0278 | 0.0386 |
BSX | 0.0257 | 0.0547 | (0.5047) | (0.0075) | 0.0152 | (0.0098) | 0.0118 | 0.0031 | 0.0342 | 0.0747 | (0.0027) | 0.0172 | 0.0105 | 0.019 | 0.0199 |
STE | 0.018 | 0.0738 | 0.0667 | 0.046 | 0.0324 | 0.0221 | 0.0185 | 0.0366 | 0.0282 | 0.0344 | 0.0245 | 0.0103 | 0.0056 | 0.0173 | 0.026 |
SNN | 0.0215 | 0.0672 | 0.0735 | 0.0433 | 0.0303 | 0.0263 | 0.0585 | 0.0514 | 0.0406 | 0.0282 | 0.0248 | 0.0341 | 0.019 | 0.0221 | 0.0324 |
CNMD | 0.2042 | 0.001 | 0.0512 | 0.0305 | 0.0261 | 0.025 | 0.0119 | 0.039 | 0.0226 | 0.009 | 0.003 | 0.0151 | (0.0303) | 0.0192 | 0.0182 |
KIDS | (0.0668) | (0.0668) | (0.0668) | (0.0668) | (0.0668) | (0.0546) | (0.0455) | (0.0966) | (0.0274) | (0.025) | (0.0442) | (0.0141) | 0.0015 | (0.0285) | (0.0299) |
Stryker, Boston Scientific Corp, and STERIS plc Earnings Yield description
The inverse of the price-to-earnings ratio, representing the percentage of each dollar invested in the stock that was earned by the company.Use Investing Themes to Complement your positions
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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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