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Decoding the 'Trump Trade': A FinBERT-Based Sentiment Analysis of Cryptocurrency Market Reactions

Adrian Besimi & Haris Haxhimehmeti

Journal of Applied Economic Sciences2026https://doi.org/10.57017/jaes.v21.2(92).03article
ABDC C
Weight
0.50

What the paper says

This study decodes the "Trump Trade" phenomenon by investigating the intersection of political sentiment and cryptocurrency market dynamics during the 2024 US presidential election. Focusing on major digital assets, (Bitcoin, Ethereum, and Dogecoin) we employ a dual-methodology approach that integrates Natural Language Processing (NLP) via the FinBERT model with traditional event study analysis and GARCH (1,1) volatility modelling. The analyse of financial news sentiment and price volatility, results show a rapid increase in volatility and positive abnormal returns following the election, correlated with Trump's pro-crypto rhetoric. A comparative analysis with the 2016 and 2020 elections reveals an intensification of the market's sensitivity to political signals, indicating that cryptocurrencies are maturing into assets responsive to policy communication. The study contributes to the growing literature on the intersection of politics and digital finance.Copyright© 2026 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.Article’s History: Received 25th of January, 2026; Revised 12th of February, 2026; Accepted 8th of March, 2026; Available online: 30th of March, 2026. Published as article in the Volume XXI, Spring, Issue 2(92), March, 2026.

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https://doi.org/https://doi.org/10.57017/jaes.v21.2(92).03

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@article{adrian2026,
  title        = {{Decoding the 'Trump Trade': A FinBERT-Based Sentiment Analysis of Cryptocurrency Market Reactions}},
  author       = {Adrian Besimi & Haris Haxhimehmeti},
  journal      = {Journal of Applied Economic Sciences},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.57017/jaes.v21.2(92).03},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.