SPY S&P 500 ETF Candlestick Medium Black Candle

As of 10 April, we identified a Medium Black Candle pattern on the SPDR S&P 500 ETF Trust SPY.

Candle usual meaning: Moderate bearish candle with body size 30-70% of range, indicating normal downward price movement

Global Stats 1-Mo Fwd:

• Directional: Up 610 (71.4%) | Down 244 (28.6%) [n=854]

• Avg Move: +1.5% (Median +1.9%)

• Expected Range (p25-p75): -0.5% to +4.0%

• Tail Risk Range (p10-p90): -3.9% to +5.8%

• Absolute Range (min-max): -32.8% to +25.2%

• Moments: Skew γ1 -1.8 | Kurt γ2 +12.2

• Risk Profile: Significant Negative Skew (Left-Tailed risk). High Leptokurtosis indicates frequent extreme tail events on both sides.

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In QHI Neutral (40-60pts zone):

• Directional: Up 103 (67.8%) | Down 49 (32.2%) [n=152]

• Avg Move: +1.3% (Median +1.9%)

• Expected Range (p25-p75): -0.7% to +4.0%

• Tail Risk Range (p10-p90): -4.6% to +6.1%

• Absolute Range (min-max): -17.5% to +11.0%

• Moments: Skew γ1 -1.0 | Kurt γ2 +2.6

• Risk Profile: Significant Negative Skew (Left-Tailed risk). Leptokurtic profile indicating heavy tails and a higher probability of extreme outliers compared to Gaussian expectations.

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Date: 2026-04-10 | Daily time scale | QHI data available since 2009-09-01 via our API.

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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 Heat Index (QHI)

The Quantlake Heat 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 fear-driven de-risking and greed-driven risk taking.

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. Provides a better sense of 'typical' performance in skewed distributions.

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.