The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets
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| Format: | Preprint |
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2026
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| _version_ | 1866912904110931968 |
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| author | Farzulla, Murad |
| author_facet | Farzulla, Murad |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2602_07018 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets Farzulla, Murad Statistical Finance Computational Finance 91B84, 91G15, 68T42, 62M10 J.4; I.6.5; G.3 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. |
| title | The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets |
| topic | Statistical Finance Computational Finance 91B84, 91G15, 68T42, 62M10 J.4; I.6.5; G.3 |
| url | https://arxiv.org/abs/2602.07018 |