@inproceedings{3b6ab2b73a954f2485fd06187d858b83,
title = "Big Data Financial Sentiment Analysis in the European Bond Markets",
abstract = "We exploit the novel Global Database of Events, Language and Tone (GDELT) to construct news-based financial sentiment measures capturing investor{\textquoteright}s opinions for three European countries, Italy, Spain and France. We study whether deterioration in investor{\textquoteright}s sentiment implies a rise in interest rates with respect to their German counterparts. Finally, we look at the link between agents{\textquoteright} sentiment and their portfolio exposure on the Italian, French and Spanish markets.",
keywords = "Financial sentiment, Government yield spread, Quantile regression, Random forest, Financial sentiment, Government yield spread, Quantile regression, Random forest",
author = "{Tiozzo Pezzoli}, Luca and Sergio Consoli and Elisa Tosetti",
year = "2020",
doi = "10.1007/978-3-030-37720-5_10",
language = "English",
isbn = "978-3-030-37719-9",
volume = "11985",
series = "LECTURE NOTES IN COMPUTER SCIENCE",
pages = "122--126",
booktitle = "Mining Data for Financial Applications",
note = "MIDAS ; Conference date: 16-09-2019 Through 20-09-2019",
}