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How Can Sentiment Analysis Contribute to Financial Markets and Services?

  • Abraham Itzhak Weinberg
  • AI Experts

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In recent years, the use of Sentiment Analysis (SA) has proliferated across a wide variety of fields, including financial markets and services. SA can help predict market trends, detect changes in consumer behavior, and identify potential investment opportunities. In this chapter, we explore the impact and applications of SA in financial markets and services and review both traditional and state-of-the-art algorithms for sentiment analysis. We demonstrate how SA approaches can help make better decisions and predictions in financial markets, stock exchange, trading, and cryptocurrencies. We provide examples of popular algorithms used in financial SA and discuss their pros and cons. In addition, we mention the main metrics for evaluating SA performance. By the end of this chapter, readers will have a deeper understanding of how sentiment analysis can contribute to financial markets and services, and the tools and techniques used to achieve accurate and reliable results.

Original languageEnglish
Title of host publicationTransformations in Banking, Finance and Regulation
PublisherWorld Scientific
Pages207-234
Number of pages28
DOIs
StatePublished - 2024
Externally publishedYes

Publication series

NameTransformations in Banking, Finance and Regulation
Volume15
ISSN (Print)2752-5821
ISSN (Electronic)2752-583X

Bibliographical note

Publisher Copyright:
© 2024 World Scientific Publishing Europe Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Sentiment analysis
  • artificial intelligence (AI)
  • financial markets
  • financial services
  • machine learning

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