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Forecasting daily volatility using high frequency financial data

Submitted by Thiago Winkler Alves (thiagowinkler@gmail.com) on 2014-09-04T13:34:50Z
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Previous issue date: 2014-08-06 / Aiming at empirical findings, this work focuses on applying the HEAVY model for daily volatility with financial data from the Brazilian market. Quite similar to GARCH, this model seeks to harness high frequency data in order to achieve its objectives. Four variations of it were then implemented and their fit compared to GARCH equivalents, using metrics present in the literature. Results suggest that, in such a market, HEAVY does seem to specify daily volatility better, but not necessarily produces better predictions for it, what is, normally, the ultimate goal. The dataset used in this work consists of intraday trades of U.S. Dollar and Ibovespa future contracts from BM&FBovespa. / Objetivando resultados empíricos, este trabalho tem foco na eaplicação do modelo HEAVY para volatilidade diária com dados financeiros do mercado Brasileiro. Muito similar ao GARCH, este modelo busca explorar dados em alta frequência para atingir seus objetivos. Quatro variações dele foram então implementadas e seus ajustes comparadados a equivalentes GARCH, utilizando métricas presentes na literatura. Os resultados sugerem que, neste mercado, o HEAVY realmente parece especificar melhor a volatilidade diária, mas não necessariamente produz melhores previsões, o que, normalmente, é o objetivo final. A base de dados utilizada neste trabalho consite de negociações intradiárias de contratos futuros de dólares americanos e Ibovespa da BM&FBovespa.

Identiferoai:union.ndltd.org:IBICT/oai:bibliotecadigital.fgv.br:10438/11994
Date06 August 2014
CreatorsAlves, Thiago Winkler
ContributorsMarques, Alessandro Martim, Takada, Hellinton Hatsuo, Escolas::EESP, Ruilova Terán, Juan Carlos
Source SetsIBICT Brazilian ETDs
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis
Sourcereponame:Repositório Institucional do FGV, instname:Fundação Getulio Vargas, instacron:FGV
Rightsinfo:eu-repo/semantics/openAccess

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