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IGV iShares Expanded Tech-Software Sector ETF

ETF

104.29 Close 10/30
Since 2024-12-02 -0.5%

Price and fund-flow snapshot

As of 2026-10-30

Every dimension sits in the neutral range.

Momentum Neutral 60-day return is Top, but 240-day return is Average.
60-day return (%) 4.9 88th percentile Top
240-day return (%) -2.91 20th percentile Average
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Neutral 20-day dollar volume is Top, but 60-day annualized volatility is Average.
60-day annualized volatility (%) 33.85 77th percentile Average
Distance from peak (%) -11.44 37th percentile Average
20-day dollar volume 835,393,015 85th percentile Top
Factor Investing Explained: 10 Classic Factors in US Stocks

iShares Expanded Tech-Software Sector ETF (IGV) today

1 quant signals active · As of 2026-10-30

Win rate and excess are historical post-trigger stats vs the market. Click a signal for its full definition and samples; history does not predict future results.

FinLab Studio

From iShares Expanded Tech-Software Sector ETF to every stock like it

AI finds several complementary traits of iShares Expanded Tech-Software Sector ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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iShares Expanded Tech-Software Sector ETF (IGV) peers and tracking

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iShares Expanded Tech-Software Sector ETF (IGV) quant signal backtests

Signals active now

Each active condition is tested against this ETF’s own history and benchmarked versus the S&P 500.

Top-quintile 6-month momentum

Active · now 95.25%

The ETF ranks in the top 20% of liquid US-listed ETFs by 126-day adjusted return.

Momentum Trading Strategy: A 12-1 Momentum Backtest
27 historical occurrences (since 2016-08-05)

Average forward return after Top-quintile 6-month momentum

20-day: Win 81.5%, Sample 27, Median +3.09%, Excess +1.46%, Beat mkt rate 74.1%

60-day: Win 85.2%, Sample 27, Median +8.58%, Excess +4.6%, Beat mkt rate 85.2%

120-day: Win 92.3%, Sample 26, Median +13.84%, Excess +5.36%, Beat mkt rate 73.1%

120 days after: historical avg +12.68%

20-day +3.08%
60-day +8.12%
120-day +12.68%
20-day
60-day
120-day
Win
81.5%
85.2%
92.3%
Sample
27
27
26
Median
+3.09%
+8.58%
+13.84%
Excess
+1.46%
+4.6%
+5.36%
Beat mkt rate
74.1%
85.2%
73.1%

Over 26 occurrences, 120-day forward avg gained 12.68%, beat the market by 5.36 pts; win rate 92.3%.

More history: Holding-period returns in its own history, Signals not active now

Holding-period returns in its own history

Since 2016-01-04, 78.1% of 2,471 one-year holding periods ended with a gain; the median one-year return was +25.7%. Over three-year holding periods, 99.5% of 1,967 ended with a gain (median +63.3%).

A holding period starts on every trading day, so periods overlap; they describe the historical distribution rather than independent outcomes.

Signals not active now

Inactive signals still show this ETF’s historical forward-return distribution for context.

52-week adjusted-price high

Pending

Adjusted close first reaches a 252-trading-day high; repeated hits within 20 days count once.

30 times historically; 60-day forward avg +3.57%, win rate 73.3%, beating the market by +0.56 pts on average.

20% below its peak

Pending

Adjusted close first falls 20% or more below its highest level so far; repeated hits within 20 days count once.

11 times historically; 60-day forward avg +9.52%, win rate 63.6%, beating the market by +4.76 pts on average.

Back above the 200-day average

Pending

Adjusted 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 +9.24%, win rate 82.4%, beating the market by +4.2 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.
  • us_fund_price:adj_close records this ETF’s distributions regularly only from 2018-12-17; returns before that date mostly reflect price changes and splits, so they understate its total return.

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.