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KIE State Street SPDR S&P Insurance ETF

ETF

65.28 USD Close 11/12
Since 2024-12-13 +15.5%

Close 11/12

FinLab Studio

From State Street SPDR S&P Insurance ETF to every stock like it

AI finds several complementary traits of State Street SPDR S&P Insurance ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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Price and fund-flow snapshot

As of 2026-11-12

Momentum: Good.

Momentum Good 60-day return is Top; 240-day return is Good.
60-day return (%) 3.6 91th percentile · Top
240-day return (%) 10.6 58th percentile · Good
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Neutral Distance from peak is Top, but 20-day dollar volume is Lagging.
60-day annualized volatility (%) 17.1 50th percentile · Good
Distance from peak (%) -1.5 84th percentile · Top
20-day dollar volume 86,847,388.0 1th percentile · Lagging
Factor Investing Explained: 10 Classic Factors in US Stocks

State Street SPDR S&P Insurance ETF (KIE) today

1 quant signals active · As of 2026-11-12

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.

State Street SPDR S&P Insurance ETF (KIE) peers and tracking

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State Street SPDR S&P Insurance ETF (KIE) 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 97.0%

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
29 historical occurrences (since 2016-10-07)

Average forward return after Top-quintile 6-month momentum

20-day: Win 64.3%, Sample 28, Median +1.6%, Excess +0.2%, Beat mkt rate 53.6%

60-day: Win 71.4%, Sample 28, Median +3.0%, Excess +1.1%, Beat mkt rate 64.3%

120-day: Win 85.2%, Sample 27, Median +6.1%, Excess +0.3%, Beat mkt rate 51.9%

120 days after: historical avg +6.3%

20-day +0.9%
60-day +3.3%
120-day +6.3%
20-day
60-day
120-day
Win
64.3%
71.4%
85.2%
Sample
28
28
27
Median
+1.6%
+3.0%
+6.1%
Excess
+0.2%
+1.1%
+0.3%
Beat mkt rate
53.6%
64.3%
51.9%

Over 27 occurrences, 120-day forward avg gained 6.3%, beat the market by 0.3 pts; win rate 85.2%.

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

Holding-period returns in its own history

Since 2016-01-04, 81.6% of 2,480 one-year holding periods ended with a gain; the median one-year return was +11.0%. Over three-year holding periods, 95.6% of 1,976 ended with a gain (median +43.9%).

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.

27 times historically; 60-day forward avg +0.4%, win rate 63.0%, beating the market by -1.3 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.

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 +4.2%, win rate 78.6%, beating the market by +1.0 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.