Daily SPY Candlestick: White Spinning Top

White Spinning Top in Extreme Greed: Median Return Compresses to +1.6% vs +2.0% Globally

Tuesday's session left a White Spinning Top on the SPY chart (+0.7%), a pattern that signals market indecision because the small real body and long shadows show uncertainty despite a bullish close.

Across 243 occurrences since 2009, the pattern resolved higher one month later 74.5% of the time, with a median return of 2.0% and an annualised Sharpe of 1.29. The return distribution leaned left, with skew at -2.1, a wide downside tail, and a 3.6% upper quartile. The pattern paired a strong 1-month up rate with occasional sharp drawdowns.

Under Extreme Greed readings in the Quantlake Herd Index (QHI), the annualised Sharpe fell to 0.33 and the average 1-month return compressed to 0.5%, even as the 1-month up rate stayed close to the global baseline at 72.3%. The distribution also became more asymmetric in this regime, with skew at -4.5, the upside range capping at 7.2%, and the worst outcome at -28.7%. The 47 observations in this regime make the directional count informative, but higher moments (skew, kurtosis) carry more uncertainty than the global baseline. Extreme Greed preserved the tendency toward higher closes one month later, with a thinner average payoff and a more concentrated left tail.

The full QHI historical series since September 1, 2009 is available via the Quantlake API for systematic integration. Learn more about the QHI methodology →
Data: 26 May 2026 · Daily Time Scale.

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.

Sharpe Ratio (annualised)
Measures risk-adjusted return — the average 1-month forward return divided by its standard deviation, scaled to an annual rate (×√12). A ratio above 1.0 indicates strong return per unit of risk; below 0.5 is weak; negative means the average outcome was a loss. It does not capture skewness or tail risk, so it should be read alongside the distribution metrics above.