What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?

Detalhes bibliográficos
Autor(a) principal: Salgado, José
Data de Publicação: 2011
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/4070
Resumo: This thesis focuses on forecasting realized volatility (RV) and implied volatility (IV) on equity markets, a subject of major importance for volatility traders. The accuracy of IV and GARCH-type models to predict RV has been researched extensively. However, little work has been done to model IV. We test the accuracy of GARCH-type models (GARCH, GJR and FCGARCH) to forecast, one-day ahead, the VIX index (the chosen IV measure) and the S&P500 index's daily realized volatility. While futures on equity's IV are widely available, futures on RV appeared recently on foreign exchange markets. Yet, expansion to equity markets is expectable. Thus, this study is a rst step on developing a RV and IV futures trading strategy. From 2001 to 2010 the models were estimated based on daily data. Forecasts evaluation is based on the mean absolute error criteria and Diebold-Mariano test. We found the GJR/FCGARCH models to have the best performance on both RV and IV. From the results, one can also infer that GARCH-type models are more suitable to foresee IV than RV. A plausible deduction is that past returns and past variance have a higher impact on IV.
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spelling What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?ForecastingRealized volatilityImplied volatilityGARCH modelsMultiple regimesPrevisãoVolatilidade realizadaVolatilidade implícitaModelos GARCHMúltiplos regimesThis thesis focuses on forecasting realized volatility (RV) and implied volatility (IV) on equity markets, a subject of major importance for volatility traders. The accuracy of IV and GARCH-type models to predict RV has been researched extensively. However, little work has been done to model IV. We test the accuracy of GARCH-type models (GARCH, GJR and FCGARCH) to forecast, one-day ahead, the VIX index (the chosen IV measure) and the S&P500 index's daily realized volatility. While futures on equity's IV are widely available, futures on RV appeared recently on foreign exchange markets. Yet, expansion to equity markets is expectable. Thus, this study is a rst step on developing a RV and IV futures trading strategy. From 2001 to 2010 the models were estimated based on daily data. Forecasts evaluation is based on the mean absolute error criteria and Diebold-Mariano test. We found the GJR/FCGARCH models to have the best performance on both RV and IV. From the results, one can also infer that GARCH-type models are more suitable to foresee IV than RV. A plausible deduction is that past returns and past variance have a higher impact on IV.Esta tese centra-se na previsão de volatilidade realizada e volatilidade implícita nos mercados de capitais, um assunto de grande importância para os traders de volatilidade. A precisão de modelos GARCH para prever a volatilidade realizada tem sido estudada extensivamente. No entanto, pouco tem sido feito para modelar volatilidade implícita. Nós testámos a precisão de modelos GARCH (GARCH, GJR e FCGARCH) para prever, com um dia de antecedência, o índice VIX (a medida de volatilidade implícita escolhida) e a volatilidade diária do S&P500. Apesar de futuros sobre volatilidade implícita estarem amplamente disponíveis, os futuros sobre volatilidade realizada só apareceram recentemente nos mercados cambiais. No entanto, a expansão para os mercados de capitais é expectável. Assim, este estudo é um primeiro passo no desenvolvimento de uma estratégia de trading de futuros sobre volatilidade realizada e volatilidade implícita. De 2001 a 2010, os modelos foram estimados com base em dados diários. A avaliação das previsões é baseada no critério do erro médio absoluto e no teste Diebold-Mariano. A conclusão é que os modelos GJR / FCGARCH prevêem melhor quer a volatilidade realizada quer a volatilidade implícita. A partir dos resultados, pode-se, também, inferir que os modelos de tipo GARCH são mais adequados para prever volatilidade implícita do que volatilidade realizada. Uma dedução plausível é que os retornos passados e a variância passada têm um maior impacto sobre volatilidade implícita.2012-11-08T15:33:36Z2011-01-01T00:00:00Z20112011-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/4070engSalgado, Joséinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:23:32Zoai:repositorio.iscte-iul.pt:10071/4070Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:10:46.083785Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
title What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
spellingShingle What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
Salgado, José
Forecasting
Realized volatility
Implied volatility
GARCH models
Multiple regimes
Previsão
Volatilidade realizada
Volatilidade implícita
Modelos GARCH
Múltiplos regimes
title_short What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
title_full What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
title_fullStr What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
title_full_unstemmed What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
title_sort What best predicts realized and implied volatility: GARCH, GJR or FCGARCH?
author Salgado, José
author_facet Salgado, José
author_role author
dc.contributor.author.fl_str_mv Salgado, José
dc.subject.por.fl_str_mv Forecasting
Realized volatility
Implied volatility
GARCH models
Multiple regimes
Previsão
Volatilidade realizada
Volatilidade implícita
Modelos GARCH
Múltiplos regimes
topic Forecasting
Realized volatility
Implied volatility
GARCH models
Multiple regimes
Previsão
Volatilidade realizada
Volatilidade implícita
Modelos GARCH
Múltiplos regimes
description This thesis focuses on forecasting realized volatility (RV) and implied volatility (IV) on equity markets, a subject of major importance for volatility traders. The accuracy of IV and GARCH-type models to predict RV has been researched extensively. However, little work has been done to model IV. We test the accuracy of GARCH-type models (GARCH, GJR and FCGARCH) to forecast, one-day ahead, the VIX index (the chosen IV measure) and the S&P500 index's daily realized volatility. While futures on equity's IV are widely available, futures on RV appeared recently on foreign exchange markets. Yet, expansion to equity markets is expectable. Thus, this study is a rst step on developing a RV and IV futures trading strategy. From 2001 to 2010 the models were estimated based on daily data. Forecasts evaluation is based on the mean absolute error criteria and Diebold-Mariano test. We found the GJR/FCGARCH models to have the best performance on both RV and IV. From the results, one can also infer that GARCH-type models are more suitable to foresee IV than RV. A plausible deduction is that past returns and past variance have a higher impact on IV.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01T00:00:00Z
2011
2011-04
2012-11-08T15:33:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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