Skip to main content

JETS U.S. Global Jets ETF

ETF

27.45

Close 10/9

Loading candles…

Price and fund-flow snapshot

As of 2026-10-09

Momentum: Weak.

Momentum Weak 240-day return is Average; 60-day return is Lagging.
60-day return (%) -12.16 4th percentile Lagging
240-day return (%) 4.52 49th percentile Average
Risk / liquidity Neutral All 3 indicators are Average.
60-day annualized volatility (%) 27.02 71th percentile Average
Distance from peak (%) -22.46 26th percentile Average
20-day dollar volume 127,712,328 22th percentile Average

U.S. Global Jets ETF (JETS) 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.

U.S. Global Jets ETF (JETS) peers and tracking

Watchlist

This page refreshes daily after the close. Add U.S. Global Jets ETF to your watchlist to track signal changes on your next visit.

U.S. Global Jets ETF (JETS) quant signal backtests

Signals active now

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

20% below its peak

Active · now -22.46%

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

8 historical occurrences (since 2016-06-24)
Average forward return after 20% below its peak。20-day: Win 50%, Sample 8, Median -3.07%, Excess -4.28%, Beat mkt rate 37.5%；60-day: Win 71.4%, Sample 7, Median +4.85%, Excess -9.18%, Beat mkt rate 42.9%；120-day: Win 60%, Sample 5, Median +5.19%, Excess -13.13%, Beat mkt rate 20%

120 days after: historical avg -0.45%

20-day -4.53%
60-day -2.9%
120-day -0.45%
20-day
60-day
120-day
Win
50%
71.4%
60%
Sample
8
7
5
Median
-3.07%
+4.85%
+5.19%
Excess
-4.28%
-9.18%
-13.13%
Beat mkt rate
37.5%
42.9%
20%

Over 5 occurrences, 120-day forward avg declined 0.45%, lagged the market by 13.13 pts; win rate 60%.

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

Holding-period returns in its own history

Since 2016-01-04, 58.6% of 2,456 one-year holding periods ended with a gain; the median one-year return was +5.4%. Over three-year holding periods, 44.8% of 1,952 ended with a gain (median -12.7%).

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.

13 times historically; 60-day forward avg -5.49%, win rate 41.7%, beating the market by -5.9 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.

34 times historically; 60-day forward avg +0.89%, win rate 60.6%, beating the market by -2.66 pts on average.

Top-quintile 6-month momentum

Pending

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

27 times historically; 60-day forward avg +2.01%, win rate 57.7%, beating the market by -1.97 pts on average.

Continue researching U.S. Global Jets ETF with the evidence above.

Continue in Studio ↗

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.