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GOLDMAN ACCESS CHINA GOV USD D UCITS ETF
CBND
Euronext Milan
CBND
Euronext Milan
CBND
Euronext Milan
CBND
Euronext Milan
Market closed
Market closed
No trades
See on Supercharts
Overview
Analysis
Discussions
Technicals
Seasonals
CBND
chart
Price
NAV
More
Full chart
1 day
0.36%
5 days
2.02%
1 month
2.54%
6 months
8.66%
Year to date
0.96%
1 year
10.34%
5 years
11.85%
All time
14.37%
Key stats
Assets under management (AUM)
79.61 M
EUR
Fund flows (1Y)
−68.98 M
EUR
Dividend yield (indicated)
2.46%
Discount/Premium to NAV
0.8%
Shares outstanding
—
Expense ratio
0.24%
About GOLDMAN ACCESS CHINA GOV USD D UCITS ETF
Issuer
The Goldman Sachs Group, Inc.
Brand
Goldman Sachs
Home page
gsam.com
Inception date
Oct 22, 2019
Index tracked
FTSE Goldman Sachs China Government Bond Index - CNY
Management style
Passive
ISIN
IE00BJSBCS90
The Sub-Fund seeks to provide investment results that closely correspond, before fees and expenses to the performance of the Index.
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Classification
Asset Class
Fixed income
Category
Government, treasury
Focus
Investment grade
Niche
Broad maturities
Strategy
Vanilla
Weighting scheme
Market value
Selection criteria
Market value
CBND
analysis
What's in the fund
Exposure type
Bonds, Cash & Other
Government
Bonds, Cash & Other
100.00%
Government
99.67%
Cash
0.33%
Technicals
Summarizing what the indicators are
suggesting.
Oscillators
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Oscillators
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Summary
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Summary
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Summary
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Moving Averages
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Moving Averages
Neutral
Sell
Buy
Strong sell
Strong buy
Strong sell
Sell
Neutral
Buy
Strong buy
Seasonals
Displays a symbol's price movements over previous years to identify recurring trends.