Sentiment Analysis of Financial News: Mechanics and Statistics

Argimiro Arratia*, Gustavo Avalosw, Alejandra Cabaña, Ariel Duarte-López, Martí Renedo-Mirambell

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

Abstract

This chapter describes the basic mechanics for building a forecasting model that uses as input sentiment indicators derived from textual data. In addition, as we focus our target of predictions on financial time series, we present a set of stylized empirical facts describing the statistical properties of lexicon-based sentiment indicators extracted from news on financial markets. Examples of these modeling methods and statistical hypothesis tests are provided on real data. The general goal is to provide guidelines for financial practitioners for the proper construction and interpretation of their own time-dependent numerical information representing public perception toward companies, stocks' prices, and financial markets in general.
Translated title of the contributionAnálisis de sentimientos en noticias financieras: mecánica y estadística.
Original languageEnglish
Title of host publicationData Science for Economics and Finance
Subtitle of host publicationMethodologies and Applications
EditorsSergio Consoli, Diego Reforgiato Recupero, Michaela Saisana
Pages195-216
ISBN (Electronic)978-3-030-66891-4
DOIs
Publication statusPublished - 2021

Cite this