Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195442
Authors: 
Cerchiello, Paola
Nicola, Giancarlo
Year of Publication: 
2018
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 6 [Year:] 2018 [Issue:] 1 [Pages:] 1-19
Abstract: 
The analysis of news in the financial context has gained a prominent interest in the last years. This is because of the possible predictive power of such content especially in terms of associated sentiment/mood. In this paper, we focus on a specific aspect of financial news analysis: how the covered topics modify according to space and time dimensions. To this purpose, we employ a modified version of topic model LDA, the so-called Structural Topic Model (STM), that takes into account covariates as well. Our aim is to study the possible evolution of topics extracted from two well known news archive-Reuters and Bloomberg-and to investigate a causal effect in the diffusion of the news by means of a Granger causality test. Our results show that both the temporal dynamics and the spatial differentiation matter in the news contagion.
Subjects: 
behavioural finance
financial news
structural topic model
granger causality
JEL: 
C83
C12
E58
E61
G02
G14
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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