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Volatility forecasting : the role of financial news in forecasting stock market volatility

datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.advisorBunkanwanicha, Pramuan
dc.contributor.advisorKokkonen, Joni
dc.contributor.authorDias, Tiago Bento da Rocha Baptista
dc.date.accessioned2017-04-27T08:13:34Z
dc.date.available2017-04-27T08:13:34Z
dc.date.issued2015-07-23
dc.date.submitted2014
dc.description.abstractThis article aims to provide a comprehensive analysis of the influence of financial news on the stock market implied volatility. We analyse each of the constituent stocks from the Dow Jones Industrial Average Index, the S&P 500 Index and use the number of firm-specific news released in the FT.com as a proxy for the information flow. To forecast the implied volatility we employ not only OLS regressions but also Neural Networks regressions. Our analysis reveals that the average number of news in the previous month is relevant in forecasting the volatility for the next month, leading to improved Out-of-Sample performances.
dc.description.abstractCet article a pour objectif d’analyser l’influence des nouvelles financières sur la volatilité implicite du marché boursier. Nous analysons toutes les valeurs du DJII et le S&P 500 Index ainsi que le nombre de nouvelles publiées dans le FT.com comme une mesure du flux d’informations. Pour faire ces estimations, nous utilisons les régressions OLS et les régressions Neural Networks. Nos résultats montrent que la moyenne des nouvelles du mois précédent est pertinente pour prévoir la volatilité du prochain mois, conduisant à meilleures performances hors de l’échantillon analysé.
dc.identifier.tid201181835pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.14/22084
dc.language.isoengpt_PT
dc.titleVolatility forecasting : the role of financial news in forecasting stock market volatilitypt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Finanças

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