Long White Candle SPY S&P 500 Up Rate Falls in QHI Extreme Greed

Long White Candle in Extreme Greed: SPY Up Rate Falls to 49% — 17 Points Below the Global Baseline

At Thursday's close, SPY printed a Long White Candle (+0.8% on the session), a large bullish candle that signals strong buying pressure.

Since 2009, across our full dataset, the pattern has appeared 579 times and delivered a median 1-month return of +1.5%, with a 1-month up rate of 65.8%. It has carried an annualised Sharpe ratio of +0.69. The distribution leans left, with skew at -0.9. Losses in weaker outcomes have been more severe than gains in stronger ones.

Against that baseline, the pattern's historical risk-adjusted edge turns negative when the Quantlake Herd Index (QHI) registers Extreme Greed, a regime that reflects crowd sentiment at its most stretched. In that regime, the 1-month up rate falls to 49.0% and the median return drops to -0.3% across 102 occurrences. The left tail deepens further, with skew at -1.1. Weak outcomes have been even more punitive relative to strong ones, and the annualised Sharpe ratio falls to -0.69.

Data: 14 May 2026 · Daily Time Scale · QHI data available since 1 Sep 2009 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.

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.