Daily SPY Candlestick: Short White Candle

Short White Candle in Greed: Return Profile Broadly Unchanged vs the Global Baseline

Friday’s Short White Candle came with a +0.5% SPY session return and signaled a small bullish candle with modest buying interest.

Our backtests since 2009 cover 677 occurrences. The pattern resolved higher after one month 71.2% of the time, with a +1.8% median return and a +1.3% average return. Direction and central tendency favored gains across the full sample. The annualized Sharpe stood at +1.07. Skew sat at -2.0, and kurtosis at +12.1. The profile paired a positive base rate with a left-tailed distribution in which infrequent losses ran larger than the typical gain.

In Quantlake Herd Index (QHI) Greed, a regime that reflects elevated crowd sentiment, the one-month profile tracked the baseline on direction and central tendency across 123 occurrences. The up rate eased to 69.9%, the median improving to +1.9%, and the average improving to +1.5%. QHI Greed changed the distribution more than the headline returns, as skew improved to -0.6 and kurtosis compressed to +0.6. The setup kept its positive edge. The left tail flattened, and the outcome spread narrowed.

Statistical analysis chart for $SPY Short White Candle. In the Greed regime (60-80 pts), this pattern shows a 1-month forward up move frequency of 69.9%.

SPY Short White Candle: 1-Month Historical Performance (All Regimes)

Metric	All Regimes (n=677)	QHI Greed (60-80) (n=123)
Up / Down	Up 482 (71.2%) \| Down 195 (28.8%) [n=677]	Up 86 (69.9%) \| Down 37 (30.1%) [n=123]
Avg / Median	+1.3% (Median +1.8%)	+1.5% (Median +1.9%)
Expected Range (p25–p75)	-0.5% to +3.6%	-0.7% to +3.7%
Tail Risk (p10–p90)	-3.3% to +5.5%	-2.6% to +5.1%
Full Range (min–max)	-28.7% to +20.1%	-7.5% to +9.0%
Skew & Kurt	Skew γ1 -2.0 \| Kurt γ2 +12.1	Skew γ1 -0.6 \| Kurt γ2 +0.6
Sharpe Ratio	+1.07	+1.68

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: 12 Jun 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.