Comparative Analysis of Cryptocurrency Market Efficiency and Local Features Using MF-DFA and DCC-GARCH

초록

This study investigates time-varying market efficiency and cross-market correlations in cryptocurrency markets across South Korea, the United States, and Japan. Using rolling-window multifractal detrended fluctuation analysis (MF-DFA) and dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH), we analyze 11 cryptocurrency-fiat pairs-Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Bitcoin Cash (BCH) denominated in Korean Won (KRW), US Dollar (USD), and Japanese Yen (JPY)-from January 2018 to September 2025. MF-DFA results confirm persistent multifractality and significant time-variation in market efficiency across all markets, consistent with the Adaptive Market Hypothesis (AMH). DCC-GARCH estimates reveal a structural divergence between return integration and efficiency correlations: return-based correlations for same-asset cross-fiat pairs are exceptionally high (mean dynamic conditional correlation of approximately 0.96-0.98), whereas efficiency-based correlations are far more heterogeneous, with cross-asset pairs approaching near-zero synchronization. We interpret the Kimchi Premium as a product of institutional frictions that impede price-level arbitrage while leaving volatility transmission largely unaffected. These findings suggest that cryptocurrency market integration is multidimensional-globally synchronized in risk dynamics, yet locally segmented in the structural quality of information processing.

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