EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS

Detalhes bibliográficos
Autor(a) principal: RESENDE,MAX C.
Data de Publicação: 2020
Outros Autores: PEDRO,EVANDRO C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RAM. Revista de Administração Mackenzie
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712020000200403
Resumo: ABSTRACT Purpose: This research aims to analyse price movements in the oil market stimulated by extreme events such as oil platform explosions, geopolitical events, and financial crises and to understand the reaction and the persistence of these effects on the commodity’s price. Originality/value: The prominent position of oil raises the concerns of investors, producers, and policymakers because of the unstable behaviour of its price level and pattern of volatility. This justifies the need to investigate the dynamics of this behaviour for the purposes of economic policy formation, strategies around trade and costs, and revenue calculations for companies of this sector, as well as investment decisions for other sources of energy. Design/methodology/approach: In order to model the occurrence of volatility jumps caused by extreme events, four specifications were used for the ARJI-GARCH conditional jumping methodology developed by Chan and Maheu (2002). The data consist of 2008 daily records of the closing price of light oil (WTI) from January 2010 to December 2017 obtained from NYMEX. Findings: Among several results it was verified that the occurrence of extreme events causes significant changes in the oil price, which goes against the efficient market hypothesis, and that a time-varying conditional jump process can be specified, but it has little sensibility to past shocks and very short-term persistence.
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spelling EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESSCrude oilVolatilityExtreme eventsARJI-GARCH modelsConditional jumpsABSTRACT Purpose: This research aims to analyse price movements in the oil market stimulated by extreme events such as oil platform explosions, geopolitical events, and financial crises and to understand the reaction and the persistence of these effects on the commodity’s price. Originality/value: The prominent position of oil raises the concerns of investors, producers, and policymakers because of the unstable behaviour of its price level and pattern of volatility. This justifies the need to investigate the dynamics of this behaviour for the purposes of economic policy formation, strategies around trade and costs, and revenue calculations for companies of this sector, as well as investment decisions for other sources of energy. Design/methodology/approach: In order to model the occurrence of volatility jumps caused by extreme events, four specifications were used for the ARJI-GARCH conditional jumping methodology developed by Chan and Maheu (2002). The data consist of 2008 daily records of the closing price of light oil (WTI) from January 2010 to December 2017 obtained from NYMEX. Findings: Among several results it was verified that the occurrence of extreme events causes significant changes in the oil price, which goes against the efficient market hypothesis, and that a time-varying conditional jump process can be specified, but it has little sensibility to past shocks and very short-term persistence.Editora MackenzieUniversidade Presbiteriana Mackenzie2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712020000200403RAM. Revista de Administração Mackenzie v.21 n.2 2020reponame:RAM. Revista de Administração Mackenzieinstname:Universidade Presbiteriana Mackenzie (UPM)instacron:MACKENZIE10.1590/1678-6971/eramf200086info:eu-repo/semantics/openAccessRESENDE,MAX C.PEDRO,EVANDRO C.eng2020-03-25T00:00:00Zoai:scielo:S1678-69712020000200403Revistahttps://www.scielo.br/j/ram/https://old.scielo.br/oai/scielo-oai.phprevista.adm@mackenzie.br1678-69711518-6776opendoar:2020-03-25T00:00RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)false
dc.title.none.fl_str_mv EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
title EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
spellingShingle EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
RESENDE,MAX C.
Crude oil
Volatility
Extreme events
ARJI-GARCH models
Conditional jumps
title_short EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
title_full EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
title_fullStr EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
title_full_unstemmed EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
title_sort EXTREME EVENTS AND THE OIL MARKET: CONDITIONAL JUMP PROCESS
author RESENDE,MAX C.
author_facet RESENDE,MAX C.
PEDRO,EVANDRO C.
author_role author
author2 PEDRO,EVANDRO C.
author2_role author
dc.contributor.author.fl_str_mv RESENDE,MAX C.
PEDRO,EVANDRO C.
dc.subject.por.fl_str_mv Crude oil
Volatility
Extreme events
ARJI-GARCH models
Conditional jumps
topic Crude oil
Volatility
Extreme events
ARJI-GARCH models
Conditional jumps
description ABSTRACT Purpose: This research aims to analyse price movements in the oil market stimulated by extreme events such as oil platform explosions, geopolitical events, and financial crises and to understand the reaction and the persistence of these effects on the commodity’s price. Originality/value: The prominent position of oil raises the concerns of investors, producers, and policymakers because of the unstable behaviour of its price level and pattern of volatility. This justifies the need to investigate the dynamics of this behaviour for the purposes of economic policy formation, strategies around trade and costs, and revenue calculations for companies of this sector, as well as investment decisions for other sources of energy. Design/methodology/approach: In order to model the occurrence of volatility jumps caused by extreme events, four specifications were used for the ARJI-GARCH conditional jumping methodology developed by Chan and Maheu (2002). The data consist of 2008 daily records of the closing price of light oil (WTI) from January 2010 to December 2017 obtained from NYMEX. Findings: Among several results it was verified that the occurrence of extreme events causes significant changes in the oil price, which goes against the efficient market hypothesis, and that a time-varying conditional jump process can be specified, but it has little sensibility to past shocks and very short-term persistence.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712020000200403
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-6971/eramf200086
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dc.publisher.none.fl_str_mv Editora Mackenzie
Universidade Presbiteriana Mackenzie
publisher.none.fl_str_mv Editora Mackenzie
Universidade Presbiteriana Mackenzie
dc.source.none.fl_str_mv RAM. Revista de Administração Mackenzie v.21 n.2 2020
reponame:RAM. Revista de Administração Mackenzie
instname:Universidade Presbiteriana Mackenzie (UPM)
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reponame_str RAM. Revista de Administração Mackenzie
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repository.name.fl_str_mv RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)
repository.mail.fl_str_mv revista.adm@mackenzie.br
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