Defiance Quantum ETF (QTUM) Dividend Yield, History & Forecast

Defiance Quantum ETF (QTUM) is an exchange-traded fund (ETF) listed on the NASDAQ Global Market. It pays a current dividend yield of 0.77% ($1.18 per share annually (TTM)). The most recent ex-dividend date was June 24, 2026, with payment scheduled for June 25, 2026. market capitalization is approximately $3.72B.

QTUM fund composition

QTUM holds 90 positions, with 14.6% of assets in its ten largest. It charges an expense ratio of 0.40%, and manages $5.22B.

Top 10 holdings

HoldingWeight
ARQQArqit Quantum Inc1.62%
NETCloudflare Inc1.57%
SNOWSnowflake Inc1.51%
RTXRTX Corp1.50%
NTNXNutanix Inc1.47%
MSFTMicrosoft Corp1.45%
AMZNAmazon.com Inc1.41%
LMTLockheed Martin Corp1.38%
RDNTRadNet Inc1.36%
NVECNVE Corp1.36%

Sector allocation

Technology81.4%Industrials8.9%Communication Services6.6%Consumer Cyclical2.0%Cash & Others1.5%Healthcare1.1%Financial Services0.0%

Frequently Asked Questions about Defiance Quantum ETF (QTUM)

What is Defiance Quantum ETF's dividend yield?
Defiance Quantum ETF (QTUM) pays a current trailing twelve-month dividend yield of 0.77%, which works out to $1.18 per share annually based on the most recent payout schedule.
When does Defiance Quantum ETF pay distributions?
The most recent ex-dividend date was June 24, 2026. The next scheduled dividend payment date is June 25, 2026.
How many years has Defiance Quantum ETF increased its dividend?
Defiance Quantum ETF (QTUM) has increased its dividend for 1 consecutive year.
What does Defiance Quantum ETF invest in?
QTUM seeks out companies involved in the development of quantum computing and machine learning technology. Quantum computing refers to hardware and software designed to harness extremely fast computers that leverage the field of quantum mechanics, a branch of physics dealing with particles and their natural behavior. Covered technologies include the development of quantum computers, application of quantum computers, interaction between quantum and traditional computers, hardware and software for machine learning, specialized machinery for semiconductor and integrated circuit packaging, and...