Predictive Crypto Crashes and Asset Pricing Implications: An Inelastic Market Perspective

Frequent and large-scale crashes are hallmarks of cryptocurrencies. We show that these crashes are predictable: assets experiencing large price swings subsequently exhibit significantly negative risk-adjusted returns at horizons up to eight weeks. These patterns are consistent with a framework featuring slow-moving capital and network effects, in which large swings reflect deteriorating trading efficiency and reduced participation. A long-elastic-winner, short-inelastic-loser strategy (EWIL) substantially outperforms momentum and persists at longer horizons. Evidence from ICO-induced Ethereum blockchain congestion causally supports this mechanism but not alternative explanations. Our results show that slow-moving capital and network effects intertwine to shape cryptocurrency pricing.