Early-Warning Signals of Political Risk in Stablecoin Markets: Human and Algorithmic Behavior Around the 2024 U.S. Election

2025-11-30

AI Summary

This study investigates the impact mechanism of the 2024 U.S. presidential election—a major political risk event—on stablecoin markets, specifically distinguishing temporal response patterns between human-driven peer-to-peer ERC-20 transactions and algorithmic automated activities. Method: We employ structural break analysis, surrogate data robustness testing, energy spectral analysis, and structural vector autoregression (SVAR) modeling. Contribution/Results: Human trading exhibits statistically significant structural shifts 48 hours prior to the election, whereas algorithmic activity adjusts only in January of the following year—revealing the first empirical evidence that human-driven stablecoin flows serve as a forward-looking early-warning signal for political risk. Concurrently, post-election periods show heightened volatility in Bitcoin and Ethereum markets, accompanied by a pronounced regime shift in stablecoin market dynamics. These findings underscore the distinct behavioral heterogeneity across market participants and highlight stablecoins’ emerging role as real-time political risk barometers.

Technology Category

• Humans and AI: Voting
• Game Theory and Economic Paradigms: Behavioral Game Theory
• Reasoning under Uncertainty: Causality

Application Category

• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Cryptocurrency and smart contracts

Abstract

We study how the 2024 U.S. presidential election, viewed as a major political risk event, affected cryptocurrency markets by distinguishing human-driven peer-to-peer stablecoin transactions from automated algorithmic activity. Using structural break analysis, we find that human-driven Ethereum Request for Comment 20 (ERC-20) transactions shifted on November 3, two days before the election, while exchange trading volumes reacted only on Election Day. Automated smart-contract activity adjusted much later, with structural breaks appearing in January 2025. We validate these shifts using surrogate-based robustness tests. Complementary energy-spectrum analysis of Bitcoin and Ethereum identifies pronounced post-election turbulence, and a structural vector autoregression confirms a regime shift in stablecoin dynamics. Overall, human-driven stablecoin flows act as early-warning indicators of political stress, preceding both exchange behavior and algorithmic responses.

Problem

• Analyzes human vs algorithmic stablecoin behavior during political risk
• Identifies early-warning signals in human-driven transactions before elections
• Examines market turbulence and regime shifts post-election in cryptocurrencies

Innovation

• Distinguishing human-driven stablecoin transactions from automated algorithmic activity
• Using structural break analysis to detect shifts in transaction timing
• Applying energy-spectrum analysis and structural vector autoregression for validation