The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets

TL;DR

This study shows that in cryptocurrency markets, sentiment extremity—captured by extreme fear or greed regimes—drives higher uncertainty and wider spreads beyond what realized volatility would predict. By decomposing total uncertainty into epistemic and aleatoric components, the paper finds that aleatoric noise dominates and that the extremity premium persists even after extensive regression controls, though regime effects are better captured nonparametrically. An agent-based model, calibrated to Bitcoin data and validated via Simulated Method of Moments, reproduces the qualitative extremity mechanism and its impact on spreads, while cross-asset validation on Ethereum confirms the pattern as a structural feature of crypto markets. Granger causality interviews reveal uncertainty predicts spreads, not vice versa, underscoring sentiment-driven liquidity withdrawal as the key channel. Extended sample validation across 2018–2026 and placebo/identification tests demonstrate the robustness of the extremity premium across market cycles, though full causal disentanglement from volatility remains challenging. Overall, the findings advocate for regime-detection approaches over complex sentiment denoising for understanding and navigating crypto-market liquidity dynamics.

Abstract

Using the Crypto Fear & Greed Index and Bitcoin daily data, we document that sentiment extremity predicts excess uncertainty beyond realized volatility. Extreme fear and extreme greed regimes exhibit significantly higher spreads than neutral periods -- a phenomenon we term the "extremity premium." Extended validation on the full Fear & Greed history (February 2018--January 2026, N = 2,896) confirms the finding: within-volatility-quintile comparisons show a significant premium (p < 0.001, Cohen's d = 0.21), Granger causality from uncertainty to spreads is strong (F = 211), and placebo tests reject the null (p < 0.0001). The effect replicates on Ethereum and across 6 of 7 market cycles. However, the premium is sensitive to functional form: comprehensive regression controls absorb regime effects, while nonparametric stratification preserves them. We interpret this as evidence that sentiment extremity captures volatility-regime interactions not fully represented by parametric controls -- consistent with, but not conclusively separable from, the F&G Index's embedded volatility component. An agent-based model reproduces the pattern qualitatively. The results suggest that intensity, not direction, drives uncertainty-linked liquidity withdrawal in cryptocurrency markets, though identification of "pure" sentiment effects from volatility remains an open challenge.

Figures (5)

• Figure 1: Time series of Corwin-Schultz spreads and total uncertainty over the 739-day sample period. The empirical correlation ($r = 0.24$) shows that spread dynamics track uncertainty dynamics at daily frequency. Spread spikes during high-uncertainty regimes (sentiment extremes) are visually apparent.
• Figure 2: Scatter plot of CS spread versus total uncertainty with OLS regression line (N = 739). The positive empirical relationship ($r = 0.24$, $R^2 = 0.055$) is consistent with spreads widening with uncertainty, though the baseline correlation is largely mechanical (Section \ref{['sec:robustness']}). The regime effects constitute the substantive finding.
• Figure 3: The Extremity Premium: Uncertainty distribution by sentiment regime (N = 715 complete cases). Extreme regimes (fear and greed) exhibit significantly higher mean uncertainty than neutral regimes, even after controlling for volatility. Diamond markers indicate regime means; dashed line shows neutral regime mean for reference.
• Figure 4: Volatility-matched regime comparison (N = 715). Within each volatility quintile, directional (extreme) regimes exhibit higher uncertainty than neutral regimes. This indicates the extremity premium is not a mechanical artifact of volatility---the pattern persists when volatility is held constant.
• Figure 5: Cross-asset validation: BTC vs. ETH regime comparison (BTC: N = 739; ETH: N = 739). Left panel shows BTC uncertainty by regime (absolute values); right panel shows ETH volatility premium relative to neutral baseline. Both assets exhibit the extremity premium pattern---extreme regimes show elevated uncertainty/volatility relative to neutral. Significance: *** $p < 0.001$, ** $p < 0.01$, * $p < 0.05$.