Hendra Maulana
Universitas Pembangunan Nasional "Veteran" Jawa Timur, Surabaya

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Dynamic Interdependence Between Altcoin Dominance and Ethereum Price: A Temporal Pattern-Based Analysis Diva Ramadhani Ristiaji Putri; Rizky Parlika; Hendra Maulana
Bulletin of Computer Science Research Vol. 6 No. 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i3.1080

Abstract

The cryptocurrency market exhibits dynamic and time-varying relationships driven by shifts in market structure and investor behavior. This study investigates the dynamic interdependence between altcoin dominance and Ethereum price, addressing the limitations of static correlation analysis by applying a temporal pattern-based approach. Using 1,416 daily observations from 2022 to 2025, the data are segmented into monthly periods to capture time-varying relationships. The analysis combines correlation, trend, and volatility metrics with pattern classification to identify recurring relationship structures across different market conditions. The results reveal a moderate negative correlation (r = ?0.48) at the aggregate level. However, the monthly analysis shows that this relationship is not stable over time, but instead varies across different market regimes. The relationship is dominated by inverse patterns (40.43%), followed by weak (38.30%) and positive (21.28%) patterns. From an economic perspective, the negative relationship can be explained by capital rotation dynamics within the cryptocurrency market. When altcoin dominance increases, market liquidity tends to shift from major assets such as Ethereum to a broader set of alternative tokens, leading to downward pressure on Ethereum prices. Conversely, during certain bullish periods, capital inflows can simultaneously strengthen both altcoin dominance and Ethereum price, resulting in positive relationships. These findings demonstrate that the relationship between altcoin dominance and Ethereum price is dynamic and context-dependent. The study highlights the importance of temporal segmentation and pattern-based analysis in capturing complex market behavior that cannot be explained by a single aggregate correlation measure.