MULTI UNITS LUXEMBOURG AMUNDI US INFLATION EXPECTATIONS 10Y ACCMULTI UNITS LUXEMBOURG AMUNDI US INFLATION EXPECTATIONS 10Y ACCMULTI UNITS LUXEMBOURG AMUNDI US INFLATION EXPECTATIONS 10Y ACC

MULTI UNITS LUXEMBOURG AMUNDI US INFLATION EXPECTATIONS 10Y ACC

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Key stats


Assets under management (AUM)
‪115.35 M‬GBP
Fund flows (1Y)
‪5.60 B‬GBP
Dividend yield (indicated)
Discount/Premium to NAV
0.2%

About MULTI UNITS LUXEMBOURG AMUNDI US INFLATION EXPECTATIONS 10Y ACC


Issuer
SAS Rue la Boétie
Brand
Amundi
Expense ratio
0.25%
Home page
Inception date
Apr 13, 2016
Index tracked
Markit iBoxx USD Breakeven 10-Year Inflation Net Total Return Index - USD
Management style
Passive
ISIN
LU1390062831
The investment objective of MULTI UNITS LUXEMBOURG - Lyxor US$ 10Y Inflation Expectations UCITS ETF is to reflect the performance of the Markit iBoxx USD Breakeven 10-Year Inflation Index (the Benchmark Index) denominated in US Dollars, in order to offer an exposure to a long position in U.S. 10-year Treasury Inflation-Protected securities

Classification


Asset Class
Fixed income
Category
Government, treasury
Focus
Investment grade
Niche
Intermediate
Strategy
Duration hedged
Weighting scheme
Duration
Selection criteria
Fixed
What's in the fund
Exposure type
Bonds, Cash & Other
Corporate
Government
Bonds, Cash & Other100.00%
Corporate62.44%
Government37.56%
Summarizing what the indicators are suggesting.
Oscillators
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Oscillators
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Summary
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Moving Averages
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Moving Averages
Neutral
SellBuy
Strong sellStrong buy
Strong sellSellNeutralBuyStrong buy
Displays a symbol's price movements over previous years to identify recurring trends.