Sentiment Spin: Attacking Financial Sentiment with Gpt-3

23 Pages Posted: 11 Mar 2023

See all articles by Markus Leippold

Markus Leippold

University of Zurich; Swiss Finance Institute

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Abstract

In this study, we explore the susceptibility of financial sentiment analysis to adversarial attacks that manipulate financial texts. With the rise of AI readership in the financial sector, companies are adapting their language and disclosures to fit AI processing better, leading to concerns about the potential for manipulation. In the finance literature, keyword-based methods, such as dictionaries, are still widely used for financial sentiment analysis due to their perceived transparency. However, our research demonstrates the vulnerability of keyword-based approaches by successfully generating adversarial attacks using the sophisticated transformer model, GPT-3.

Keywords: Sentiment analysis in financial markets, keyword-based approach, FinBERT, GPT-3

Suggested Citation

Leippold, Markus, Sentiment Spin: Attacking Financial Sentiment with Gpt-3. Available at SSRN: https://ssrn.com/abstract=4384956 or http://dx.doi.org/10.2139/ssrn.4384956

Markus Leippold (Contact Author)

University of Zurich ( email )

Rämistrasse 71
Zürich, CH-8006
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

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