IWV iShares Russell 3000 ETF
Close 11/10
From iShares Russell 3000 ETF to every stock like it
AI finds several complementary traits of iShares Russell 3000 ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.
Screen stocks like iShares Russell 3000 ETFPrice and fund-flow snapshot
Every dimension sits in the neutral range.
Momentum Neutral 240-day return is Good, but 60-day return is Average.
Risk / liquidity Neutral Distance from peak is Good, but 20-day dollar volume is Lagging.
iShares Russell 3000 ETF (IWV) peers and tracking
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iShares Russell 3000 ETF (IWV) quant signal backtests
Holding-period returns in its own history
Since 2016-01-04, 86.3% of 2,478 one-year holding periods ended with a gain; the median one-year return was +16.7%. Over three-year holding periods, 99.9% of 1,974 ended with a gain (median +46.3%).
A holding period starts on every trading day, so periods overlap; they describe the historical distribution rather than independent outcomes.
More history: Signals not active now
Signals not active now
Inactive signals still show this ETF’s historical forward-return distribution for context.
52-week adjusted-price high
PendingAdjusted close first reaches a 252-trading-day high; repeated hits within 20 days count once.
28 times historically; 60-day forward avg +0.9%, win rate 71.4%, beating the market by +0.1 pts on average.
20% below its peak
PendingAdjusted close first falls 20% or more below its highest level so far; repeated hits within 20 days count once.
7 times historically; 60-day forward avg +12.9%, win rate 100.0%, beating the market by +0.8 pts on average.
Back above the 200-day average
PendingAdjusted close crosses from below to above its 200-day moving average; repeated crosses within 20 days count once.
16 times historically; 60-day forward avg +2.5%, win rate 62.5%, beating the market by +0.3 pts on average.
Top-quintile 6-month momentum
PendingThe ETF ranks in the top 20% of liquid US-listed ETFs by 126-day adjusted return.
Method and limits
- Returns use us_fund_price:adj_close (finlab data.set_market('us_fund')), adjusted for splits and for distributions where the data includes them.
- Excess returns use world_index:^GSPC, the S&P 500 price index without dividends, as the benchmark.
- Percentiles and the 6-month momentum signal compare against the most liquid US-listed ETFs by 20-day dollar volume; mutual funds are excluded.
- Category labels come from the fund data where it provides one (bond, income, crypto) and from the fund name for leveraged, inverse and commodity ETFs.
- Overlapping event windows are descriptive distributions, not independent samples.
This page is for historical data analysis and education only. It is not investment advice. Backtests and historical return distributions do not predict future performance; evaluate risk independently before trading.