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Mining News Data for the Measurement and Prediction of Inflation Expectations

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Mining News Data for the Measurement and Prediction of Inflation Expectations

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dc.contributor.author Gabrielyan, Diana es_ES
dc.contributor.author Masso, Jaan es_ES
dc.contributor.author Uusküla, Lenno es_ES
dc.date.accessioned 2020-07-28T07:54:07Z
dc.date.available 2020-07-28T07:54:07Z
dc.date.issued 2020-06-30
dc.identifier.isbn 9788490488324
dc.identifier.uri http://hdl.handle.net/10251/148762
dc.description.abstract [EN] In this paper we use high frequency multidimensional textual news data and propose an index of inflation news. We utilize the power of text mining and its ability to convert large collections of text from unstructured to structured form for in-depth quantitative analysis of online news data. The significant relationship between the household’s infla-tion expectations and news topics is documented and the forecasting performance of news-based indices is evaluated for different horizons and model variations. Results sug-gest that with optimal number of topics a machine learning model is able to forecast the inflation expectations with greater accuracy than the simple autoregressive models. Addi-tional results from forecasting headline inflation indicate that the overall forecasting accu-racy is at a good level. Findings in this paper support the view in the literature that the news are good indicators of inflation and are able to capture inflation expectations well. es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Web data es_ES
dc.subject Internet data es_ES
dc.subject Big data es_ES
dc.subject Qca es_ES
dc.subject Pls es_ES
dc.subject Sem es_ES
dc.subject Conference es_ES
dc.subject Inflation es_ES
dc.subject Inflation expectations es_ES
dc.subject Natural language processing es_ES
dc.subject News data es_ES
dc.subject Topic modelling es_ES
dc.title Mining News Data for the Measurement and Prediction of Inflation Expectations es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2020.2020.11322
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Gabrielyan, D.; Masso, J.; Uusküla, L. (2020). Mining News Data for the Measurement and Prediction of Inflation Expectations. Editorial Universitat Politècnica de València. 2-4. https://doi.org/10.4995/CARMA2020.2020.11322 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Julio 08-09,2020 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2020/paper/view/11322 es_ES
dc.description.upvformatpinicio 9 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\11322 es_ES


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