Publications

Authors:

Moreno-Pérez, Carlos; Minozzo, Marco

Title:

Natural language processing and financial markets: semi-supervised modelling of Coronavirus and economic news

Year:

2024

Type of item:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Language:

Inglese

Format:

A Stampa

Referee:

Sì

Name of journal:

ADVANCES IN DATA ANALYSIS AND CLASSIFICATION

ISSN of journal:

1862-5347

Page numbers:

1-25

Keyword:

COVID-19, EGARCH, Latent Dirichlet Allocation, investor attention, uncertainty indices, Word Embedding

Short description of contents:

This paper investigates the reactions of US financial markets to press news from January 2019 to 1 May 2020. To this end, we deduce the content and uncertainty of the news by developing apposite indices from the headlines and snippets of The New York Times, using unsupervised machine learning techniques. In particular, we use Latent Dirichlet Allocation to infer the content (topics) of the articles, and Word Embedding (implemented with the Skip-gram model) and K-Means to measure their uncertainty. In this way, we arrive at the definition of a set of daily topic-specific uncertainty indices. These indices are then used to find explanations for the behaviour of the US financial markets by implementing a batch of EGARCH models. In substance, we find that two topic-specific uncertainty indices, one related to COVID-19 news and the other to trade war news, explain the bulk of the movements in the financial markets from the beginning of 2019 to end-April 2020. Moreover, we find that the topic-specific uncertainty index related to the economy and the Federal Reserve is positively related to the financial markets, meaning that our index is able to capture actions of the Federal Reserve during periods of uncertainty.

Product ID:

135892

Handle IRIS:

11562/1111426

Last Modified:

November 22, 2024

Bibliographic citation:

Moreno-Pérez, Carlos; Minozzo, Marco, Natural language processing and financial markets: semi-supervised modelling of Coronavirus and economic news «ADVANCES IN DATA ANALYSIS AND CLASSIFICATION» , 2024 , pp. 1-25

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