Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/20383
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Mao, X. | - |
dc.contributor.author | Czellar, V. | - |
dc.contributor.author | Ruiz, E. | - |
dc.contributor.author | Veiga, H. | - |
dc.date.accessioned | 2020-04-20T11:16:26Z | - |
dc.date.available | 2020-04-20T11:16:26Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 2452-3062 | - |
dc.identifier.uri | http://hdl.handle.net/10071/20383 | - |
dc.description.abstract | The statistical properties of a general family of asymmetric stochastic volatility (A-SV) models which capture the leverage effect in financial returns are derived providing analytical expressions of moments and autocorrelations of power-transformed absolute returns. The parameters of the A-SV model are estimated by a particle filter-based simulated maximum likelihood estimator and Monte Carlo simulations are carried out to validate it. It is shown empirically that standard SV models may significantly underestimate the value-at-risk of weekly S&P 500 returns at dates following negative returns and overestimate it after positive returns. By contrast, the general specification proposed provide reliable forecasts at all dates. Furthermore, based on daily S&P 500 returns, it is shown that the most adequate specification of the asymmetry can change over time. | eng |
dc.language.iso | eng | - |
dc.publisher | Elsevier | - |
dc.relation | UID/GES/00315/2013 | - |
dc.rights | openAccess | - |
dc.subject | Particle filtering | eng |
dc.subject | Leverage effect | eng |
dc.subject | SV models | eng |
dc.subject | Value-at-risk | eng |
dc.title | Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation | eng |
dc.type | article | - |
dc.pagination | 84 - 105 | - |
dc.peerreviewed | yes | - |
dc.journal | Econometrics and Statistics | - |
dc.volume | 13 | - |
degois.publication.firstPage | 84 | - |
degois.publication.lastPage | 105 | - |
degois.publication.title | Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation | eng |
dc.date.updated | 2020-04-20T12:15:37Z | - |
dc.description.version | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.doi | 10.1016/j.ecosta.2019.08.002 | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Matemáticas | por |
dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Economia e Gestão | por |
dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Outras Ciências Sociais | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-69298 | - |
iscte.alternateIdentifiers.wos | WOS:000510837900006 | - |
iscte.alternateIdentifiers.scopus | 2-s2.0-85072063846 | - |
Aparece nas coleções: | BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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1-s2.0-S2452306219300486-main.pdf | Versão Editora | 3,79 MB | Adobe PDF | Ver/Abrir |
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