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

TL;DR

This paper treats the 2024 U.S. election as a political-risk shock and shows that human-driven stablecoin activity on ERC-20 transactions acts as an early-warning signal for market turbulence, preceding exchange trading and automated responses. By jointly applying Bai–Perron structural-break detection, Hilbert–Huang time-frequency analysis, AAFT surrogate testing, and SVAR, the authors document a sequential pattern: anticipatory shifts in human on-chain flows (EOA–EOA) around 2024-11-03, followed by trading-volume breaks on Election Day and later adjustments in automated SC–SC activity (January 2025). The results indicate a regime shift in stablecoin dynamics with 28–48% higher spillovers post-election and identify USDT as the primary transmission channel. These findings offer a practical on-chain early-warning framework for investors, risk managers, and policymakers navigating political uncertainty in decentralized finance.

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.

Figures (4)

• Figure 1: The figure illustrates the structural breakpoint, Hilbert spectrum, and instantaneous energy for blockchain USDT BTC trading data. (a) Logarithm of the daily trading volume in USD, $\log(V_\mathrm{USD})$. The brown line represents the rolling mean of the trading volume, the red dashed line indicates the U.S. Presidential election Day 2024, and the blue dashed line marks the structural breakpoint. (b) Hilbert Spectrum for BTC, showing the instantaneous frequency ($\omega$) over time. A period of high energy is observed during the U.S. Presidential election. (c) Normalized instantaneous energy for BTC. A sudden energy surge occurs after the election period begins, peaking on November 10, 2024. This peak exceeds the statistical threshold energy level, defined as $E_\mathrm{th} = E_\mu + 4\sigma$.
• Figure 2: The figure illustrates the structural breakpoint, Hilbert spectrum, and instantaneous energy for blockchain USDC and ETH trading data. (a) Logarithm of the daily trading volume in USD, $\log(V_\mathrm{USD})$. The brown line represents the rolling mean of the trading volume, the red dashed line indicates the U.S. Presidential election Day 2024, and the blue dashed line marks the structural breakpoint. (b) Hilbert Spectrum for ETH, showing the instantaneous frequency ($\omega$) over time. A period of high energy is observed during the U.S. Presidential election. (c) Normalized instantaneous energy for ETH. A sudden energy surge occurs after the election period begins, peaking on November 7, 2024. This peak exceeds the statistical threshold energy level, defined as $E_\mathrm{th} = E_\mu + 4\sigma$.
• Figure 3: Structural break analysis of stablecoin trading volumes. The BP test detects significant structural breaks in (a) USDT and (b) USDC trading volumes on 5 November 2024, coinciding with the U.S. Presidential election. The red dashed line marks the election date, and the blue line would indicate the break date; however, because the two coincide, only the red dashed line is visible. These synchronized breaks confirm that the blockchain anticipatory signal was followed by a broad market adjustment in centralized exchange activity.
• Figure 4: Structural Break Analysis of Automated SC–SC Stablecoin Transactions. The Bai–Perron test identifies significant post-election structural breaks in automated SC–SC transaction volumes for (a) USDT on 16 January 2025, and (b) USDC on 2 January 2025. The red dashed line marks the 2024 U.S. election date, while the blue line indicates the respective break dates. These delayed adjustments indicate that bot-driven systems responded only after market stabilization, contrasting with the immediate, human-driven shifts observed before the election.