Loomis Sayles (Ireland) Financial Indicators Patterns

F00000PTQL -- Ireland Fund  

USD 8.60  0.10  1.15%

Please makes use of Loomis Sayles Multisect Inc Fd FDM USD fundamental data analysis to find out if markets are presently mispricing the entity. We found seven available fundamentals for Loomis Sayles which can be compared to its peers in the industry. Please exercise Loomis Sayles Multisect Inc Fd FDM USD Last Dividend Paid and the relationship between Cash Position Weight and Equity Positions Weight to make a decision on weather Loomis Sayles Multisect is priced favorably. Use Loomis Sayles to protect your portfolios against small markets fluctuations. The fund experiences somewhat bearish sentiment, but market may correct it shortly. Check odds of Loomis Sayles to be traded at $8.34 in 30 days.

Loomis Sayles Company Summary

Loomis Sayles competes with Brown Advisory, Aegon Intl, Aegon Intl, Payden Absolute, and Sanlam Global. The Fund invests at least 80 percent of its total assets in bonds and other related fixed income securities. Loomis Sayles is traded on Irland Stock Exchange in Ireland.

Loomis Sayles Equity Positions Weight vs Minimum Initial Investment

Loomis Sayles Multisect Inc Fd FDM USD is one of the top funds in equity positions weight among similar funds. It is one of the top funds in minimum initial investment among similar funds making about  110.62  of Minimum Initial Investment per Equity Positions Weight.

Loomis Sayles Market Fundamentals

 Quote8.60
 Change(%) 1.15%
 Change0.10 
 Open8.7
 Low8.6
 High8.6
 Volume1.000
 ExchangeISE

Distress Rating

Loomis Sayles Financial Distress Probability

45%
Chance of Financial Distress
Loomis Sayles Multisect Inc Fd FDM USD has less than 45 (%) percent chance of experiencing financial distress in the next 2 years of operations. More Info

Loomis Sayles Opportunity Range

March 21, 2019 Opportunity Range

Additionally see Investing Opportunities. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.
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