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August 25, 2026
4 min read
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Daily SPY Candlestick: Short Black Candle

Short Black Candle in Extreme Greed: Risk-Adjusted Edge Negative, Sharpe -0.06 vs +1.07 Globally

SPY rose 0.3% on Tuesday and printed a Short Black Candle, a small bearish candle with modest selling pressure.

 

Across 660 occurrences since 2009, the pattern resolves higher 70.5% of the time, with a 1.9% median return, a 1.3% average return, and a 1.07 Sharpe. The baseline favors positive outcomes on both frequency and risk-adjusted return. Skew at -2.2 and kurtosis at +14.9 pair that positive baseline with a fat left tail, and the average sits below the median because a small set of downside outliers weighs on expectancy.

 

SPY's 1-month up rate is 59.1% when the Quantlake Herd Index registers Extreme Greed, below the 70.5% global rate across 127 occurrences, and the historical risk-adjusted edge is negative in this regime at a -0.06 Sharpe versus +1.07 globally. The median return is 0.7%, while the average is -0.1%. A majority of occurrences close higher, yet expectancy turns negative because the left tail is larger than the winning moves, with skew at -3.1 and the p10 floor at -6.2%. Extreme Greed cuts the full-sample edge through weaker frequency and a harsher downside distribution, so the pattern's broad positive baseline does not hold in stretched sentiment.

 

Statistical analysis chart for $SPY Short Black Candle. In the Extreme Greed regime (80-100 pts), this pattern shows a 1-month forward up move frequency of 59.1%.

SPY Short Black Candle: 1-Month Historical Performance

MetricAll Regimes (n=660)QHI Extreme Greed (80-100) (n=127)
Up / DownUp 465 (70.5%) | Down 195 (29.5%) [n=660]Up 75 (59.1%) | Down 52 (40.9%) [n=127]
Avg / Median+1.3% (Median +1.9%)-0.1% (Median +0.7%)
Expected Range (p25–p75)-0.5% to +3.7%-2.1% to +3.3%
Tail Risk (p10–p90)-3.2% to +5.3%-6.2% to +5.1%
Full Range (min–max)-31.7% to +16.5%-31.7% to +9.4%
Skew & KurtSkew γ1 -2.2 | Kurt γ2 +14.9Skew γ1 -3.1 | Kurt γ2 +16.0
Sharpe Ratio+1.07-0.06

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: 25 Aug 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.

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