SEI GMF (Ireland) Financial Diagnostics

IE00B4T42J36 -- Ireland Fund  

GBp 1,146  1.00  0.09%

The current investor indifference towards the small price fluctuations of SEI GMF may raise some interest from investors. The Fund closed today at a share price of 1145.0 on 1.000 in trading volume. The fund administrators and managers did not add any value to SEI GMF Glb investors in April. However, most investors can still diversify their portfolios with SEI GMF to hedge your portfolio against high-volatility market scenarios. The fund standard deviation of daily returns for 30 days (very short) investing horizon is currently 0.0. The very small Fund volatility is a good signal to investors with longer term investment horizons. This diagnostics interface makes it easy to digest most current publicly released information about SEI GMF as well as get updates on important government artifacts including earning estimates, SEC corporate filings and announcements. This module also helps to analysis SEI GMF price relationship with some important fundamental indicators such as market cap and management efficiency. Please also check Risk vs Return Analysis.

SEI GMF Note

The fund retains about 35.83% of assets under management (AUM) in cash. SEI GMF Glb last dividend was 0.03 per share. The Base Currency of the Fund is U.S. Dollars. Under normal market conditions, the Fund will invest at least 80% of its net assets in investmentgrade fixed income securities and money market instruments that are listed or traded on Recognised Markets. No more than 10% of the Fund will be invested in securities that are rated below investment grade or are unrated by both Moody?s and Standard & Poor?s.

SEI GMF Glb Alerts

SEI GMF Glb is not yet fully synchronised with the market data
The fund retains about 35.83% of its assets under management (AUM) in cash

SEI GMF Technical and Predictive Indicators

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Risk-Return Analysis

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Please also check Risk vs Return Analysis. 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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