SPY Gap Up History: Follow-Through and Fade Data

SPY Gaps Are Rare — But Informative

As a broad index ETF, SPY gaps much less frequently than individual stocks. Over 2016-2026, SPY has opened more than 1% above the prior close on roughly 3% of all trading days, and more than 2% on less than 1% of days. Each of these gaps typically corresponds to a meaningful overnight catalyst: Fed decisions, earnings from mega-caps, geopolitical events, or economic data.

When SPY does gap, it's almost always carrying information. The question is whether to chase it or fade it.

Base Rates: Gap-Ups Slightly Fade Intraday, Continue Over 5 Days

SPY gap-ups of 1%+ have historically produced a same-day open-to-close return averaging roughly -0.1% with a 49% win rate — essentially flat. There's a very mild intraday fade tendency, but it's too small to trade reliably.

The 5-day return after a 1%+ SPY gap up has averaged roughly +0.6% with a 58% win rate. The 10-day return has averaged around +0.9% with a 57% win rate. These are modest but positive edges — the market's short-term momentum persists after gap-ups.

• Same-day open-to-close after 1%+ gap up: ~-0.1%, ~49% win rate
• 5-day return after 1%+ gap up: ~+0.6% average, ~58% win rate
• 10-day return after 1%+ gap up: ~+0.9% average, ~57% win rate
• Gap frequency: ~3% of days with 1%+ gap up

The 2%+ Gap Is the Key Signal

Larger SPY gaps carry more information than smaller ones. A 2%+ gap up has historically been followed by a 5-day return averaging roughly +1.4% with a 64% win rate — meaningfully stronger than the 1% gap base rate. A 3%+ gap (extremely rare, roughly 5 instances in the decade) has averaged even stronger 5-day returns, though the sample is too small for high-confidence conclusions.

Large SPY gaps usually come from macro catalysts: emergency Fed actions, major political events, or extreme earnings seasons. The follow-through reflects the market's digestion of the new information over the following days.

Gap Fades Are More Common in Uncertain Regimes

Conditioning on VIX shows an important distinction. When SPY gaps up during low-VIX regimes (VIX < 15), the 5-day follow-through has averaged roughly +0.8% with a 62% win rate. When it gaps up during high-VIX regimes (VIX > 25), the 5-day follow-through has averaged closer to -0.2% with a 48% win rate.

This makes intuitive sense. Calm markets tend to be 'buy the dip, buy the gap' markets where momentum persists. Volatile markets tend to be mean-reverting, where gap-ups often fade as traders use strength to sell into the rally.

Using the Data

The simplest approach: when SPY gaps up, check the current VIX regime and the pattern analogs. If VIX is low and analogs skew positive, the gap has strong historical support. If VIX is high and analogs skew mixed, the gap is more likely to fade.

from chartlibrary import ChartLibrary cl = ChartLibrary(api_key="cl_...") spy = cl.intelligence("SPY") regime = cl.market_regime() print(f"VIX: {regime['vix']}") print(f"SPY 5d avg: {spy.forward_returns['5d']['mean']:.1%}")

Related reading: our posts on market regime tracking and do chart patterns predict returns offer useful framing for index-level pattern analysis.