EFV iShares MSCI EAFE Value ETF
Price and fund-flow snapshot
As of 2026-10-30
Every dimension sits in the neutral range.
Momentum Neutral 240-day return is Good, but 60-day return is Average.
Risk / liquidity Neutral 60-day annualized volatility is Good, but 20-day dollar volume is Average.
From iShares MSCI EAFE Value ETF to every stock like it
AI finds several complementary traits of iShares MSCI EAFE Value ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.
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iShares MSCI EAFE Value ETF (EFV) quant signal backtests
Holding-period returns in its own history
Since 2016-01-04, 70.5% of 2,471 one-year holding periods ended with a gain; the median one-year return was +13.2%. Over three-year holding periods, 85.1% of 1,967 ended with a gain (median +19.8%).
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.
30 times historically; 60-day forward avg +0.58%, win rate 69%, beating the market by -1.3 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 +5.72%, win rate 57.1%, beating the market by +1.49 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.
17 times historically; 60-day forward avg +3.44%, win rate 52.9%, beating the market by +1.1 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.
13 times historically; 60-day forward avg +2.14%, win rate 76.9%, beating the market by -1.85 pts on average.
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.