dc.contributor.author | Arteche González, Jesús María ![ORCID](/themes/Mirage2//images/orcid_16x16.png) | |
dc.contributor.author | García Enríquez, Javier ![ORCID](/themes/Mirage2//images/orcid_16x16.png) | |
dc.date.accessioned | 2024-01-26T09:35:36Z | |
dc.date.available | 2024-01-26T09:35:36Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Journal of Forecasting 41(1) : 3-16 (2022) | es_ES |
dc.identifier.issn | 1099-131X | |
dc.identifier.issn | 0277-6693 | |
dc.identifier.uri | http://hdl.handle.net/10810/64356 | |
dc.description.abstract | [EN] Estimation of the value at risk (VaR) requires prediction of the future volatility. Whereas this is a simple task in ARCH and related models, it becomes much more complicated in stochastic volatility (SV) processes where the volatility is a function of a latent variable that is not observable. In-sample (present and past values) and out-of-sample (future values) predictions of that unobservable variable are thus necessary. This paper proposes singular spectrum analysis (SSA), which is a fully nonparametric technique that can be used for both purposes. A combination of traditional forecasting techniques
and SSA is also considered to estimate the VaR. Their performance is assessed in an extensive Monte Carlo and with an application to a daily series of S&P500 returns. | es_ES |
dc.description.sponsorship | Basque Government, Grant/Award Number: IT1359-19; Spanish Ministry of Science and Innovation and ERDF, Grant/Award Number: ECO2016-76884-P; National Research Agency, Grant/Award Number: PID2019-105183GB-I00 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Wiley | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | forecasting | es_ES |
dc.subject | signal extraction | es_ES |
dc.subject | singular spectrum analysis | es_ES |
dc.subject | stochastic volatility | es_ES |
dc.subject | value at risk | es_ES |
dc.title | Singular spectrum analysis for value at risk in stochastic volatility models | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2021 John Wiley & Sons, Ltd. | es_ES |
dc.relation.publisherversion | https://onlinelibrary.wiley.com/doi/10.1002/for.2796 | es_ES |
dc.identifier.doi | 10.1002/FOR.2796 | |
dc.departamentoes | Métodos Cuantitativos | es_ES |
dc.departamentoeu | Metodo Kuantitatiboak | es_ES |