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.
Cross Equities Shareholders Equity Per Share Analysis
Select Fundamental
2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PSFE | 35.883 | 35.883 | 35.883 | 35.883 | 35.883 | 35.883 | 35.883 | 35.883 | 35.883 | 34.1198 | 31.8641 | 42.6097 | 14.2043 | 14.3782 | 13.66 |
NNAVW | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | 0.583 | (19.6151) | 4.2425 | 0.99 | 0.7292 | 0.77 |
QTWO | (0.9539) | (0.9539) | (1.6731) | 0.1795 | 2.6982 | 3.165 | 2.5281 | 2.5868 | 3.7129 | 8.2127 | 12.3679 | 10.1127 | 7.3128 | 7.6855 | 8.07 |
NXPL | (96.8 M) | (4.8 K) | (11.5 K) | (5.7 K) | 1.5 K | 1.7 K | 453 | 149 | 110 | 30.1252 | 2.1096 | 4.2959 | 2.6769 | 1.8397 | 1.93 |
ALVO | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (27.7518) | (4.3396) | (2.8546) | (4.1033) | (4.31) |
SPNS | 14.3077 | 4.031 | 2.9645 | 4.2576 | 3.7322 | 3.7782 | 3.9715 | 4.0853 | 4.0637 | 4.5072 | 7.4929 | 7.4604 | 7.3091 | 8.0775 | 9.25 |
UBER | 4.6109 | 4.6109 | 4.6109 | 4.6109 | 4.6109 | 4.6109 | 4.6109 | (7.8344) | 9.4604 | 11.367 | 6.9973 | 7.6394 | 3.7219 | 5.526 | 4.15 |
Paysafe, NextNav Warrant, and Q2 Holdings Shareholders Equity Per Share description
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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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