This paper analyzes how thematic crypto asset categories responded to the 2024 U.S. presidential election using cumulative abnormal returns (CARs) within an event study framework. We examine four thematic categories: Made in U.S., DeFi & Real-World Assets, AI & Big Data, and World Liberty Financial. The results show significant negative CARs in the pre-election window, followed by sharp positive reversals on the election day and after the election. The most pronounced post-election recoveries appear in the Made in U.S. category with CARs over 40 %, suggesting market reassessment of regulatory expectations. Innovation-driven categories such as (World Liberty Financial, DeFi & Real-World Assets, and AI & Big Data) exhibit more muted responses. These findings underscore how political alignment influences crypto performance and offer new evidence on the pricing of political risk in digital asset markets.

Pirazzi Maffiola, K., Sevim, H. O., Policy-sensitive crypto assets: Event study of thematic returns around U.S. elections, <<ECONOMICS LETTERS>>, 2026; 258 (112723): 1-10. [doi:10.1016/j.econlet.2025.112723] [https://hdl.handle.net/10807/325999]

Policy-sensitive crypto assets: Event study of thematic returns around U.S. elections

Pirazzi Maffiola, Kevin
Primo
;
2026

Abstract

This paper analyzes how thematic crypto asset categories responded to the 2024 U.S. presidential election using cumulative abnormal returns (CARs) within an event study framework. We examine four thematic categories: Made in U.S., DeFi & Real-World Assets, AI & Big Data, and World Liberty Financial. The results show significant negative CARs in the pre-election window, followed by sharp positive reversals on the election day and after the election. The most pronounced post-election recoveries appear in the Made in U.S. category with CARs over 40 %, suggesting market reassessment of regulatory expectations. Innovation-driven categories such as (World Liberty Financial, DeFi & Real-World Assets, and AI & Big Data) exhibit more muted responses. These findings underscore how political alignment influences crypto performance and offer new evidence on the pricing of political risk in digital asset markets.
2026
Inglese
Pirazzi Maffiola, K., Sevim, H. O., Policy-sensitive crypto assets: Event study of thematic returns around U.S. elections, <<ECONOMICS LETTERS>>, 2026; 258 (112723): 1-10. [doi:10.1016/j.econlet.2025.112723] [https://hdl.handle.net/10807/325999]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/325999
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