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IBB iShares Biotechnology ETF

ETF

206.49

Close 10/9

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Price and fund-flow snapshot

As of 2026-10-09

Momentum: Strong.

Momentum Strong All 2 indicators are Top.
60-day return (%) 8.97 85th percentile Top
240-day return (%) 33.04 86th percentile Top
Risk / liquidity Neutral 20-day dollar volume is Good, but 60-day annualized volatility is Average.
60-day annualized volatility (%) 25.31 70th percentile Average
Distance from peak (%) -4.82 64th percentile Good
20-day dollar volume 354,389,849 65th percentile Good

iShares Biotechnology ETF (IBB) today

1 quant signals active · As of 2026-10-09

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.

iShares Biotechnology ETF (IBB) peers and tracking

Watchlist

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iShares Biotechnology ETF (IBB) 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 87.16%

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

25 historical occurrences (since 2016-09-13)
Average forward return after Top-quintile 6-month momentum。20-day: Win 52%, Sample 25, Median +0.07%, Excess -0.94%, Beat mkt rate 40%；60-day: Win 50%, Sample 24, Median +0.44%, Excess -0.93%, Beat mkt rate 50%；120-day: Win 56.5%, Sample 23, Median +1.06%, Excess -3.5%, Beat mkt rate 26.1%

120 days after: historical avg +1.68%

20-day +0.32%
60-day +0.26%
120-day +1.68%
20-day
60-day
120-day
Win
52%
50%
56.5%
Sample
25
24
23
Median
+0.07%
+0.44%
+1.06%
Excess
-0.94%
-0.93%
-3.5%
Beat mkt rate
40%
50%
26.1%

Over 23 occurrences, 120-day forward avg gained 1.68%, lagged the market by 3.5 pts; win rate 56.5%.

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

Holding-period returns in its own history

Since 2016-01-04, 68.4% of 2,456 one-year holding periods ended with a gain; the median one-year return was +7.7%. Over three-year holding periods, 76.8% of 1,952 ended with a gain (median +18.1%).

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.

24 times historically; 60-day forward avg -0.43%, win rate 39.1%, beating the market by -3.14 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.

12 times historically; 60-day forward avg +9.92%, win rate 75%, beating the market by +2.02 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.

29 times historically; 60-day forward avg +4.27%, win rate 62.1%, beating the market by +0.59 pts on average.

Continue researching iShares Biotechnology ETF with the evidence above.

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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 2019-12-30; 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.