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SPYI Neos S&P 500(R) High Income ETF

ETF

52.43 Close 10/30
Since 2024-12-02 +26.1%

Price and fund-flow snapshot

As of 2026-10-30

Momentum: Good, Risk / liquidity: Good.

Momentum Good All 2 indicators are Good.
60-day return (%) 0.07 70th percentile Good
240-day return (%) 13.02 61th percentile Good
Momentum Trading Strategy: A 12-1 Momentum Backtest
Risk / liquidity Good Distance from peak is Good, but 20-day dollar volume is Average.
60-day annualized volatility (%) 7.93 25th percentile Good
Distance from peak (%) -2.18 76th percentile Good
20-day dollar volume 156,903,452 33th percentile Average
FinLab Studio

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AI finds several complementary traits of Neos S&P 500(R) High Income ETF across different dimensions, combines them into a multifactor strategy, and backtests it against the market.

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Neos S&P 500(R) High Income ETF (SPYI) quant signal backtests

Signals active now

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

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

Holding-period returns in its own history

Since 2022-08-30, 99.6% of 795 one-year holding periods ended with a gain; the median one-year return was +16.1%. Over three-year holding periods, 100.0% of 291 ended with a gain (median +58.6%).

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.

9 times historically; 60-day forward avg +3.1%, win rate 87.5%, beating the market by -0.7 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.

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.