Sentiment analysis of financial news: Mechanics and statistics

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

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libroCapítuloInvestigaciónrevisión exhaustiva

3 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaData Science for Economics and Finance
Subtítulo de la publicación alojadaMethodologies and Applications
EditorialSpringer International Publishing AG
Páginas195-216
Número de páginas22
ISBN (versión digital)9783030668914
ISBN (versión impresa)9783030668907
DOI
EstadoPublicada - 9 jun 2021

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