How Can Sentiment Analysis Contribute to Financial Markets and Services?

Abraham Itzhak Weinberg

Chapter 5 in Artificial Intelligence and Beyond for Finance, 2024, pp 207-234 from World Scientific Publishing Co. Pte. Ltd.

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.

Keywords: Artificial Intelligence; Machine Learning; Deep Learning; Reinforcement Learning; Sentiment Analysis; Portfolio Management; Financial Forecasting (search for similar items in EconPapers)
JEL-codes: C63 C8 G11 G17 (search for similar items in EconPapers)
Date: 2024
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