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August 4, 2026
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Daily SPY Candlestick: Bullish Strong Line

Bullish Strong Line in Greed: Return Profile In Line with the Global Baseline

SPY rose 1.8% on Tuesday and printed a Bullish Strong Line. The pattern signals bullish conviction through a large real body and clear buyer dominance.

 

Across 291 occurrences since 2009, the pattern resolves higher after one month 67.4% of the time, with a 1.4% median return, a 1.0% average return, and a 0.84 annualized Sharpe. The base rate favors gains, and the risk-adjusted profile is positive. The interquartile range runs from -0.9% to +3.5%, and skew sits at -0.8 with kurtosis at +2.5. Upside outcomes occupy the middle of the distribution; the left tail is heavier than the right tail.

 

Greed contains 63 observations, so the directional count is informative. Skew and kurtosis carry more uncertainty than the global baseline. For SPY after this pattern, the 1-month up rate is 65.1% in Greed versus 67.4% globally, while the 1.5% median return sits near baseline and the 0.6% average return runs below the global average. Kurtosis at 0.1 versus 2.5 globally marks the main regime difference. Greed trims the fat-tail character of the full sample, so the distribution is flatter and the positive expectancy is weaker.

 

Statistical analysis chart for $SPY Bullish Strong Line. In the Greed regime (60-80 pts), this pattern shows a 1-month forward up move frequency of 65.1%.

SPY Bullish Strong Line: 1-Month Historical Performance

Note: limited sample size (n<100) for moment stability.

MetricAll Regimes (n=291)QHI Greed (60-80) (n=63)
Up / DownUp 196 (67.4%) | Down 95 (32.6%) [n=291]Up 41 (65.1%) | Down 22 (34.9%) [n=63]
Avg / Median+1.0% (Median +1.4%)+0.6% (Median +1.5%)
Expected Range (p25–p75)-0.9% to +3.5%-1.9% to +3.3%
Tail Risk (p10–p90)-4.4% to +5.4%-5.1% to +4.4%
Full Range (min–max)-18.0% to +14.8%-9.2% to +7.1%
Skew & KurtSkew γ1 -0.8 | Kurt γ2 +2.5Skew γ1 -0.8 | Kurt γ2 +0.1
Sharpe Ratio+0.84+0.55

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: 4 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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