Intraday volatility forecasting in high-frequency data using order book information
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/73498 |
Resumo: | This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future considering a multiplicative component GARCH framework, where the conditional volatility of high-frequency returns is decomposed into a daily, diurnal and stochastic intraday component. In contrast to extant research, in this work project a relatively long period of 423 trading days is covered corresponding to about 345.000 1-minute observations. To opt for a more practitioner-oriented approach we perform fixed window as well as rolling window forecasts. There is evidence that incorporating Limit Order Book information into the return series leads to superior forecasting results compared to the usage of simple trade returns. Nonetheless, the forecasting performance is time-varying and is often deteriorated by the seasonality of liquidity provision |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Intraday volatility forecasting in high-frequency data using order book informationGarchVolatility forecastingHigh-frequency dataLimit order bookDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future considering a multiplicative component GARCH framework, where the conditional volatility of high-frequency returns is decomposed into a daily, diurnal and stochastic intraday component. In contrast to extant research, in this work project a relatively long period of 423 trading days is covered corresponding to about 345.000 1-minute observations. To opt for a more practitioner-oriented approach we perform fixed window as well as rolling window forecasts. There is evidence that incorporating Limit Order Book information into the return series leads to superior forecasting results compared to the usage of simple trade returns. Nonetheless, the forecasting performance is time-varying and is often deteriorated by the seasonality of liquidity provisionRodrigues, Paulo Manuel MarquesRUNGrübe, Maximilian2019-06-24T14:42:36Z2019-01-142019-01-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/73498TID:202226158enginfo: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:RCAAP2024-03-11T04:34:01Zoai:run.unl.pt:10362/73498Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:35:20.352438Repositório 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 |
Intraday volatility forecasting in high-frequency data using order book information |
title |
Intraday volatility forecasting in high-frequency data using order book information |
spellingShingle |
Intraday volatility forecasting in high-frequency data using order book information Grübe, Maximilian Garch Volatility forecasting High-frequency data Limit order book Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
Intraday volatility forecasting in high-frequency data using order book information |
title_full |
Intraday volatility forecasting in high-frequency data using order book information |
title_fullStr |
Intraday volatility forecasting in high-frequency data using order book information |
title_full_unstemmed |
Intraday volatility forecasting in high-frequency data using order book information |
title_sort |
Intraday volatility forecasting in high-frequency data using order book information |
author |
Grübe, Maximilian |
author_facet |
Grübe, Maximilian |
author_role |
author |
dc.contributor.none.fl_str_mv |
Rodrigues, Paulo Manuel Marques RUN |
dc.contributor.author.fl_str_mv |
Grübe, Maximilian |
dc.subject.por.fl_str_mv |
Garch Volatility forecasting High-frequency data Limit order book Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Garch Volatility forecasting High-frequency data Limit order book Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future considering a multiplicative component GARCH framework, where the conditional volatility of high-frequency returns is decomposed into a daily, diurnal and stochastic intraday component. In contrast to extant research, in this work project a relatively long period of 423 trading days is covered corresponding to about 345.000 1-minute observations. To opt for a more practitioner-oriented approach we perform fixed window as well as rolling window forecasts. There is evidence that incorporating Limit Order Book information into the return series leads to superior forecasting results compared to the usage of simple trade returns. Nonetheless, the forecasting performance is time-varying and is often deteriorated by the seasonality of liquidity provision |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-06-24T14:42:36Z 2019-01-14 2019-01-14T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/73498 TID:202226158 |
url |
http://hdl.handle.net/10362/73498 |
identifier_str_mv |
TID:202226158 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799137974631268352 |