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Running Oak Efficient Growth (RUNN) ETF Holdings & Analysis

ETFOther

$34.45-0.20%
1-year price historyRange $31.47 – $35.53
52-week range$34.45
$31.45$35.73

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What RUNN does

RUNN is an actively managed investment strategy with a goal of long-term growth of capital.

Fund profile

Category
Other
AUM
$335.31M
Holdings
10
52-week high
$35.73
52-week low
$31.45

Top holdings

Top 1019%
HoldingWeight
Equifax, Inc.2.01%
Leidos Holdings, Inc.1.98%
Roper Technologies, Inc.1.98%
Accenture plc1.91%
State Street Institutional Treasury Money Market Fund1.87%
FTI Consulting, Inc.1.87%
CACI International, Inc.1.86%
Arthur J Gallagher & Company1.86%
ServiceNow, Inc.1.85%
ResMed, Inc.1.83%

Sector allocation

Industrials33.89%
Technology26.74%
Healthcare14.95%
Financial Services13.22%
Consumer Cyclical7.97%
Basic Materials1.66%
Communication Services1.56%
Cash & Others0.01%

Geographic allocation

United States91.72%
Ireland3.41%
Other1.86%
Switzerland1.80%
United Kingdom1.21%

PortView Portfolio Insights

PortView analyzes how RUNN fits your actual portfolio — position weight, ETF overlap with your other funds, sector and geographic exposure, concentration, and how this fund contributes to your portfolio risk and return. Connect a portfolio to see your personalized figures; PortView never shows another user's private holdings.

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Related securities

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Frequently asked questions

What does RUNN track?
RUNN is the Running Oak Efficient Growth ETF, a Other ETF.
What is the expense ratio of RUNN?
Expense ratio data for RUNN is shown on the page when available from our data provider.
What are the largest holdings in RUNN?
Top holdings include EFX, LDOS, ROP, ACN, TRIXX.
How can PortView analyze RUNN overlap with other ETFs?
PortView computes the holdings overlap between RUNN and the other ETFs and stocks you own, plus your combined sector and geographic exposure, so you can see true diversification.

The information provided by PortView is for informational and educational purposes only and does not constitute investment advice. Market data may be delayed. Past performance does not guarantee future results.