Analysis of Stock Indices during the SVB Bank Run in March 2023 based on Sentiment Analysis

This paper examines the Silicon Valley Bank (SVB) bank run event on March 9, 2023, and seeks to contribute to the understanding of market dynamics during this crisis. The bank run was unique and chilling because of two factors: first, the event was amplified by widespread panic on Twitter following a message by Peter Thiel, a renowned technology entrepreneur; and second, the speed of withdrawals was unprecedented because of the power of social media and the technology that allowed quick reactions. In this paper, we start by examining the market volatility and the impact of the SVB crisis on key indices in the United States and Europe. Then, we analyse the Twitter activity and the corresponding sentiment that emerged throughout the event. Our data indicates that Twitter sentiment accurately mirrored the market's fluctuation and volatility. Moreover, employing readily available Large Language Models (LLMs) for sentiment analysis can potentially serve as an early indicator of market shifts and provide a cautionary signal in the event of a similar occurrence in the future.

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Publication Details

Journal
Proceedings of the ... international conference on economics and social sciences.
Published
2024-09-09
DOI
https://doi.org/10.24818/icess/2024/068
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Stock Indices during the SVB Bank Run in March 2023 based on Sentiment Analysis

Andreea-Mădălina BOZAGIU, Zorina Alliata
Proceedings of the ... international conference on economics and social sciences.
E-commerce and Technology Innovations
article

Analysis of Stock Indices during the SVB Bank Run in March 2023 based on Sentiment Analysis

Andreea-Mădălina BOZAGIU, Zorina Alliata
article en

Abstract

This paper examines the Silicon Valley Bank (SVB) bank run event on March 9, 2023, and seeks to contribute to the understanding of market dynamics during this crisis. The bank run was unique and chilling because of two factors: first, the event was amplified by widespread panic on Twitter following a message by Peter Thiel, a renowned technology entrepreneur; and second, the speed of withdrawals was unprecedented because of the power of social media and the technology that allowed quick reactions. In this paper, we start by examining the market volatility and the impact of the SVB crisis on key indices in the United States and Europe. Then, we analyse the Twitter activity and the corresponding sentiment that emerged throughout the event. Our data indicates that Twitter sentiment accurately mirrored the market's fluctuation and volatility. Moreover, employing readily available Large Language Models (LLMs) for sentiment analysis can potentially serve as an early indicator of market shifts and provide a cautionary signal in the event of a similar occurrence in the future.

Proceedings of the ... international conference on economics and social sciences.
Decent work and economic growth
Openalex Percentile: Top 74%
E-commerce and Technology Innovations
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