<p>Modeling dependence among cryptocurrency returns has attracted growing attention, yet most studies rely on Pearson’s correlation or parametric copula methods that impose restrictive linearity and symmetry assumptions. This paper provides a comprehensive nonparametric analysis of pairwise return dependence for the ten most capitalized cryptocurrencies, using nearly two years of daily data, covering all 45 distinct pairs. Our methodological contribution is threefold. First, we implement and compare eleven nonparametric copula density estimators simultaneously across all pairs, providing the most comprehensive nonparametric comparison to date for cryptocurrency markets. Second, we complement these density visualizations with Patton (2012) quantile dependence plots and the formal tail asymmetry measure of Kato, Yoshiba and Eguchi (2022), which supplies bootstrap and asymptotic confidence intervals. Third, we go beyond Pearson correlation by reporting four model-free dependence measures, Spearman’s, Kendall’s, Chatterjee’s, and the Bergsma-Dassios rank correlation, for all 45 pairs, documenting and explaining cases of substantial divergence from linear correlation. Our main empirical findings are as follows. First, lower-tail dominance, joint crash risk exceeding joint boom risk, is the rule rather than the exception: across at least 35 of the 45 pairs, the Kato et al. (2022) measure is predominantly negative, with statistical significance at deep quantile levels, directly recommending asymmetric copula families such as Clayton, rotated Gumbel, or BB7 over symmetric alternatives. Second, the cryptocurrency market admits a clean three-way taxonomy: BTC ETH-type pairs with high, approximately symmetric tail dependence; high-beta altcoin pairs (SOL, DOGE, ADA, XRP) with extreme asymmetric upper-tail co-movement driven by speculative sentiment contagion; and stablecoin pairs, particularly those involving USDC, are exhibiting near-independence. Third, several XRP pairs display pronounced Pearson-Spearman divergences of up to 0.14, revealing nonlinear rank-order dependence that standard linear correlation systematically underestimates. Fourth, USDT, despite its stablecoin status, exhibits statistically significant positive co-movement with all non-USDC assets, consistent with Tether issuance dynamics and stress-induced volume during market sell-offs.</p>