Daily SPY Candlestick: Bearish Strong Line

Bearish Strong Line in Greed: Risk-Adjusted Edge Inverts, Sharpe -0.06 vs +1.13 Globally

Wednesday’s Bearish Strong Line came with a -1.2% SPY session and signaled bearish conviction. The large real body showed seller dominance.

Across 202 instances since 2009, the pattern resolved higher one month later 69.8% of the time and carried a +2.2% median return, a +1.6% average return, and a +1.13 Sharpe. The base rate favored upside, with positive central tendency and positive risk-adjusted payoff. The distribution leaned left, with skew at -0.9 and kurtosis at +3.3, so the positive expectancy coexisted with a fatter losing tail than the upside frequency alone implied. That combination left the full-sample edge dependent on many positive outcomes overpowering a smaller set of larger drawdowns.

In Quantlake Herd Index (QHI) Greed, a crowd-sentiment regime that captures elevated optimism, the historical risk-adjusted edge turned negative. The 1-month up rate fell to 60.0%, the median compressed to +0.9%, the average slipped to -0.1%, and the Sharpe fell to -0.06 across 45 occurrences. A majority of occurrences resolved higher, yet expectancy turned negative because the losing tail was larger than the winning moves were frequent, with skew at -1.8 and the p10 floor at -6.8%. The 45 observations made the directional count informative, but higher moments, skew and kurtosis, carried more uncertainty than the global baseline. The regime change centered on weaker central tendency and a heavier left tail.

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: 17 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.