Global X Funds Global X Autonomous & Electric Vehicles ETF
Snapshot*
Top 10 Holdings
What is DRIV?
The Global X Autonomous & Electric Vehicles ETF (DRIV) seeks to invest in companies involved in the development of autonomous vehicle technology, electric vehicles ( EVs ), and EV components and materials. This includes companies involved in the development of autonomous vehicle software and hardware, as well as companies that produce EVs, EV components such as lithium batteries, and critical EV materials such as lithium and cobalt.
ETFs related toDRIV
ETFs correlated to DRIV include HIBL, SPHB, XT
What is ETF correlation?
Correlation is a measure of the strength of the relationship between two ETFs. It quantifies the degree to which prices of the two ETFs typically move together.
Here, correlation is measured over the past year with the Pearson correlation coefficient (Pearon’s r), which ranges from -1 to 1.
Using ETF correlations in portfolio and strategy construction
ETF correlations can help you create investing strategies and portfolios. Use them to:
- •Build a diversified portfolio from uncorrelated or inversely correlated ETFs with the aim of minimizing portfolio risk.
- •Compare correlated or related ETFs to find one with a lower expense ratio or higher trading volume.
- •Create an investing strategy that hedges an ETF with an uncorrelated or inversely correlated ETF.
FAQ
Disclaimers
We show information directly obtained from our data provider, Xignite. Data shown here is provided by Xignite, an unaffiliated third party. Composer believes the information shown here is reliable, but has not been verified and there is no guarantee that the information is accurate.
We show information based on calculations performed by Composer using data from our provider. Information provided here is based on calculations performed by Composer using data sourced from Xignite, an unaffiliated third party. Composer believes this information is reliable, but has not verified the data and there is no guarantee that the calculations are accurate.