Search
Products
Community
Markets
News
Brokers
More
IN
Get started
Markets
/
Italy
/
ETF market
/
XS2L
XTRACK S&P500 2X LEV DAY SWAP UCITS ETF
XS2L
Euronext Milan
XS2L
Euronext Milan
XS2L
Euronext Milan
XS2L
Euronext Milan
Market closed
Market closed
No trades
See on Supercharts
Overview
Analysis
Discussions
Technicals
Seasonals
XS2L
chart
Price
NAV
More
Full chart
1 day
0.56%
5 days
3.78%
1 month
9.33%
6 months
27.96%
Year to date
56.03%
1 year
76.95%
5 years
202.76%
All time
2.16 K%
Key stats
Assets under management (AUM)
418.85 M
EUR
Fund flows (1Y)
20.06 M
EUR
Dividend yield (indicated)
—
Discount/Premium to NAV
0.8%
About XTRACK S&P500 2X LEV DAY SWAP UCITS ETF
Issuer
Deutsche Bank AG
Brand
Xtrackers
Expense ratio
0.60%
Home page
etf.dws.com
Inception date
Mar 18, 2010
Index tracked
S&P 500 2x Leveraged Daily Index - USD
Management style
Passive
ISIN
LU0411078552
The aim is for your investment to reflect the performance of the S&P 500 2x Leveraged Daily Index (Index).
Show more
Classification
Asset Class
Equity
Category
Size and style
Focus
Large cap
Niche
Broad-based
Strategy
Vanilla
Weighting scheme
Market cap
Selection criteria
Committee
XS2L
analysis
What's in the fund
Exposure type
Stocks
Finance
Technology Services
Utilities
Health Technology
Stock breakdown by region
100%
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.