Beyond the Random Walk: Asymmetric and Cross-Correlated Dynamics in Cryptocurrencies

Abstract

This study provides a novel application of quantile-panel persistence method to evaluate statedependent predictability in major cryptocurrency prices while accounting for cross-sectional dependence. Although conventional mean-based tests suggest mean reversion on average, the quantile evidence indicates a clear asymmetry: downside shocks are relatively transitory whereas upside shocks tend to persist, consistent with conditional departures from the random walk. Cross-sectional dependence is statistically significant across quantiles, reinforcing the importance of controlling for market-wide drivers in panel inference. Interpreted through a finance perspective, these results are consistent with state-dependent pricing dynamics in which demand pressures, liquidity conditions, and common market shocks shape adjustment across regimes. To assess economic significance, we translate the identified predictable states into two simple, rulebased trading overlays. Both strategies frequently improve risk-adjusted performance relative to buy-and-hold, indicating that distribution-aware persistence measures can be mapped into implementable allocation rules without relying on aggressive directional positioning.