SPY S&P 500 ETF Candlestick Tweezers Top

On April 22 the SPY (S&P 500 ETF) printed a session high that matched the prior day's high and then reversed lower into the close, leaving repeated rejection at the same price level.

Pattern interpretation: Bearish reversal - Two candles with similar highs show resistance level

Statistical analysis chart for $SPY Tweezers Top. In the Greed regime (60-80 pts), this pattern shows a 1-month forward up move frequency of 69.6%.

Global Statistics — 1-Month Forward

Note: limited sample size (n<100) for moment stability.

Metric	All Regimes (n=236)	QHI Greed (60-80) (n=46)
Up / Down	Up 165 (69.9%) \| Down 71 (30.1%) [n=236]	Up 32 (69.6%) \| Down 14 (30.4%) [n=46]
Avg / Median	+0.9% (Median +1.4%)	+0.9% (Median +1.7%)
Expected Range (p25–p75)	-0.4% to +3.3%	-1.1% to +3.1%
Tail Risk (p10–p90)	-3.3% to +4.9%	-3.7% to +4.7%
Full Range (min–max)	-28.7% to +6.9%	-7.4% to +5.8%
Skew & Kurt	Skew γ1 -3.3 \| Kurt γ2 +22.9	Skew γ1 -1.0 \| Kurt γ2 +0.6
Risk Profile	Deceptive Typical Returns; narrow P25 masks extreme left-tail fragility.	Significant Negative Skew (Left-Tailed risk).

Date: 2026-04-22 | Daily time scale | QHI data available since 2009-09-01 via our API.

Romain Gandon — CEO, Quantlake

Disclaimer: This article is for informational and educational purposes only and does not constitute investment advice. Past performance is not indicative of future results.

Definitions

Quantlake Herd Index (QHI)

The Quantlake Herd Index (QHI) is a proprietary cross-asset behavioral sentiment composite ranging from 0 to 100 that measures extremes in investor psychology across the U.S. financial system.

It aggregates signals from U.S. equity momentum and breadth, equity market concentration dynamics, credit market risk appetite (high-yield vs investment-grade demand), implied volatility conditions, and credit spread behavior. These inputs are normalized into a single behavioral risk barometer reflecting the balance between risk-averse and risk-on investor behavior.

Because markets are influenced by behavioral biases, sentiment extremes frequently precede mean reversion in forward returns.

QHI Regimes

0–20: Extreme Fear

20–40: Fear

40–60: Neutral

60–80: Greed

80–100: Extreme Greed

Statistical Terms

Median
The midpoint of the return distribution — 50% of outcomes fell above and 50% below this value. Less sensitive to extreme outliers than the average.

p25 / p75 (Interquartile Range)
The range within which the middle 50% of historical outcomes fell. p25 marks the 25th percentile (bottom of the range); p75 marks the 75th percentile (top). A tighter range indicates a more predictable pattern; a wide range reflects high dispersion.

p10 / p90 (Tail Interval)
The range encompassing the middle 80% of historical outcomes. P10 represents the 10th percentile (the "downside" threshold), while P90 represents the 90th percentile (the "upside" threshold). Unlike the Interquartile Range, this metric captures the shoulders of the distribution, providing a clearer view of potential tail risk and extreme performance potential.

Skew (γ1 — Skewness)
Measures the asymmetry of the return distribution. A negative skew (γ1 < 0) signals a left-tailed distribution — most outcomes cluster on the positive side, but the rare negative outcomes can be severely large. A positive skew (γ1 > 0) is the opposite.

Kurt (γ2 — Excess Kurtosis)
Measures tail density relative to a normal distribution. A high positive value (Leptokurtic) indicates fat tails — extreme events occur more frequently than a normal distribution would predict. A negative value (Platykurtic) indicates thinner tails.

Mesokurtic
A kurtosis value typically within a range of -0.5 to +0.5, consistent with a normal (Gaussian) distribution. Tail risk is neither elevated nor suppressed relative to standard statistical models.

Gaussian (Normal Distribution)
The classic bell-curve distribution. When a pattern's moments are described as "consistent with Gaussian expectations," it means tail risk behaves as standard statistical models would predict — no unusual concentration of extreme outcomes.