BNY Mellon (Ireland) Financial Indicators Patterns

IE0032177440 -- Ireland Fund  

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We found nine available fundamental indicators for BNY Mellon US Dollar Liquidity H which can be compared to its rivals. Please makes use of BNY Mellon US Total Asset and the relationship between Three Year Return and Ten Year ReturnTotal Asset, Five Year Return, Net Asset, as well as the relationship between Three Year Return and Ten Year Return to make a decision on weather BNY Mellon is priced fairly. Use BNY Mellon to protect your portfolios against small markets fluctuations. The fund experiences normal downward trend, but the immediate impact on correlations cannot be determined at the moment . Check odds of BNY Mellon to be traded at $0.99 in 30 days.

BNY Mellon Company Summary

BNY Mellon competes with GS USD. The investment objective of the sub- Fund is to provide investors with as high a level of current income in U.S. BNY Mellon is traded on Irland Stock Exchange in Ireland.

BNY Mellon Cash Position Weight vs Five Year Return

BNY Mellon US Dollar Liquidity H is rated second overall fund in cash position weight among similar funds. It is rated second overall fund in five year return among similar funds . The ratio of Cash Position Weight to Five Year Return for BNY Mellon US Dollar Liquidity H is about  462.10 

BNY Mellon Market Fundamentals

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Distress Rating

BNY Mellon Financial Distress Probability

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Chance of Financial Distress
BNY Mellon US Dollar Liquidity H has less than 1 (%) percent chance of experiencing financial distress in the next 2 years of operations. More Info
BNY Mellon US Dollar Liquidity H is rated second overall fund in net asset among similar funds. Total Asset Under Management (AUM) of USD Money Market - Short Term category is currently estimated at about 38.84 Billion. BNY Mellon retains roughly 6.86 Billion in net asset claiming about 18% of USD Money Market - Short Term category.

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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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