Financial dynamics and interconnectedness between layer-1 and layer-2 blockchains

This study investigates the financial dynamics and interdependencies between Layer-1 (L1) blockchains (Bitcoin and Ethereum) and their respective Layer-2 (L2) solutions through the lens of multifractal analysis. Using high-frequency 15-minute price data from leading L2 projects (including Arbitrum, Immutable, Loopring, Metis, Mantle, Skale, Polygon, Stacks), we examine both univariate multifractality and bivariate cross-correlations. The results reveal that L1 and L2 cryptocurrencies exhibit significant nonlinear dependencies and multifractal characteristics across different moments and time scales. Specifically, while persistent cross-correlations dominate under small market fluctuations, extreme fluctuations are marked by anti-persistent dynamics. The strength of multifractality is found to vary across pairs, with ETH-linked L2 solutions (particularly Arbitrum and Immutable) demonstrating the most pronounced multifractal behavior. Moreover, shuffled and surrogate tests confirm that the sources of multifractality primarily stem from long-memory effects and heavy-tailed distributions, indicating an empirical rather than intrinsic form of multifractality. These findings provide novel insights into the complexity of blockchain ecosystems, offering implications for portfolio diversification, systemic risk assessment, and the financial viability of L2 scalability solutions.

Authors

Institutions

Publication Details

Journal
International Review of Economics & Finance
Published
2026-01-21
DOI
https://doi.org/10.1016/j.iref.2026.104899
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Financial dynamics and interconnectedness between layer-1 and layer-2 blockchains

Turker Acikgoz
International Review of Economics & Finance
Complex Systems and Time Series Analysis
article

Financial dynamics and interconnectedness between layer-1 and layer-2 blockchains

Turker Acikgoz
article en

Abstract

This study investigates the financial dynamics and interdependencies between Layer-1 (L1) blockchains (Bitcoin and Ethereum) and their respective Layer-2 (L2) solutions through the lens of multifractal analysis. Using high-frequency 15-minute price data from leading L2 projects (including Arbitrum, Immutable, Loopring, Metis, Mantle, Skale, Polygon, Stacks), we examine both univariate multifractality and bivariate cross-correlations. The results reveal that L1 and L2 cryptocurrencies exhibit significant nonlinear dependencies and multifractal characteristics across different moments and time scales. Specifically, while persistent cross-correlations dominate under small market fluctuations, extreme fluctuations are marked by anti-persistent dynamics. The strength of multifractality is found to vary across pairs, with ETH-linked L2 solutions (particularly Arbitrum and Immutable) demonstrating the most pronounced multifractal behavior. Moreover, shuffled and surrogate tests confirm that the sources of multifractality primarily stem from long-memory effects and heavy-tailed distributions, indicating an empirical rather than intrinsic form of multifractality. These findings provide novel insights into the complexity of blockchain ecosystems, offering implications for portfolio diversification, systemic risk assessment, and the financial viability of L2 scalability solutions.

International Review of Economics & FinanceVol. 107
Başkent University (TR)
Openalex Percentile: Top 84%
Complex Systems and Time Series Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.