The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets
Abstract
Multi-scale sentiment analysis framework for agent-based modeling of cryptocurrency market microstructure. Blends institutional macro signals (ASRI framework) with retail micro signals (CryptoBERT with MC Dropout). In stylized simulation, multi-scale blending reduces volatility from 877% to 5.8% (p=0.013) and spreads from 147 to 3.5 bps (p<0.001) compared to single-source sentiment. Regime-adaptive weighting adjusts the macro/micro blend based on detected market conditions.
Suggested citation
Murad Farzulla (2025). The Extremity Premium: Sentiment Regimes and Adverse Selection in Cryptocurrency Markets. Dissensus Working Paper DAI-2510. DOI: 10.21203/rs.3.rs-8802783/v1
Methodology
Agent-based modeling
Monte Carlo Dropout
Mesa ABM
CryptoBERT
ASRI integration
Topics
Financial Markets
Cryptocurrency
Agent-Based Modeling