Assessing News Contagion in Finance
| Autor: | Giancarlo Nicola, Paola Cerchiello |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Topic model
Economics and Econometrics G02 Context (language use) 02 engineering and technology behavioural finance financial news structural topic model granger causality Granger causality Covariate ddc:330 0202 electrical engineering electronic engineering information engineering Economics E58 C12 Finance lcsh:HB71-74 business.industry G14 05 social sciences Causal effect Financial news lcsh:Economics as a science Focus (linguistics) C83 E61 Predictive power 020201 artificial intelligence & image processing 0509 other social sciences 050904 information & library sciences business |
| Zdroj: | Econometrics; Volume 6; Issue 1; Pages: 5 Econometrics, Vol 6, Iss 1, p 5 (2018) |
| ISSN: | 2225-1146 |
| DOI: | 10.3390/econometrics6010005 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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