Detecting Structural Changes in Bitcoin, Altcoins, and the S&P 500 Using the GSADF Test: A Comparative Analysis of 2024 Trends

Understanding structural regime shifts in crypto asset markets is vital for early detection of systemic risk. This study applies the Generalized Sup Augmented Dickey–Fuller (GSADF) test to daily high-frequency price data of five major crypto assets—BTC, ETH, SOL, AAVE, and BCH—from 2023 to 2025. The results reveal asset-specific structural breaks: BTC and BCH aligned with macroeconomic shocks, while DeFi tokens (e.g., AAVE, SOL) exhibited fragmented, project-driven shifts. The S&P 500 index, in contrast, showed no persistent regime shifts, indicating greater structural stability. To examine inter-asset linkages, we construct co-occurrence matrices based on GSADF breakpoints. These reveal strong co-explosivity between BTC and other assets, and unexpectedly weak synchronization between ETH and AAVE, underscoring the sectoral idiosyncrasies of DeFi tokens. While the GSADF test remains central to our analysis, we also employ a Markov Switching Model (MSM) as a secondary tool to capture short-term volatility clustering. Together, these methods provide a layered view of long- and short-term market dynamics. This study highlights crypto markets’ structural heterogeneity and proposes scalable computational frameworks for real-time monitoring of explosive behavior.

Authors

Institutions

Publication Details

Journal
Journal of risk and financial management
Published
2025-08-12
DOI
https://doi.org/10.3390/jrfm18080450
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
6.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detecting Structural Changes in Bitcoin, Altcoins, and the S&P 500 Using the GSADF Test: A Comparative Analysis of 2024 Trends

A. Yamaguchi
2 citations
Journal of risk and financial management
Blockchain Technology Applications and Security
6.49
article

Detecting Structural Changes in Bitcoin, Altcoins, and the S&P 500 Using the GSADF Test: A Comparative Analysis of 2024 Trends

A. Yamaguchi
article en
2 citations

Abstract

Understanding structural regime shifts in crypto asset markets is vital for early detection of systemic risk. This study applies the Generalized Sup Augmented Dickey–Fuller (GSADF) test to daily high-frequency price data of five major crypto assets—BTC, ETH, SOL, AAVE, and BCH—from 2023 to 2025. The results reveal asset-specific structural breaks: BTC and BCH aligned with macroeconomic shocks, while DeFi tokens (e.g., AAVE, SOL) exhibited fragmented, project-driven shifts. The S&P 500 index, in contrast, showed no persistent regime shifts, indicating greater structural stability. To examine inter-asset linkages, we construct co-occurrence matrices based on GSADF breakpoints. These reveal strong co-explosivity between BTC and other assets, and unexpectedly weak synchronization between ETH and AAVE, underscoring the sectoral idiosyncrasies of DeFi tokens. While the GSADF test remains central to our analysis, we also employ a Markov Switching Model (MSM) as a secondary tool to capture short-term volatility clustering. Together, these methods provide a layered view of long- and short-term market dynamics. This study highlights crypto markets’ structural heterogeneity and proposes scalable computational frameworks for real-time monitoring of explosive behavior.

Journal of risk and financial managementVol. 18(8)
University of Edinburgh (GB)
Intel Corporation
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
6.49
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.