Modelling volatility dependence with score copula models
Abstract: I study score-driven models for modelling high persistence dependence between financial volatility series. I model this persistence dependence with two components, one for the long memory and the other for the short-term process. The addition of components offers a parsimonious solution for modelling high persistence and also allows for a short-term component for the transient shocks. I apply the model to emerging equities in the Americas. The estimates are robust to the advent of the pandemic. In addition, data resampling and marginal alternatives deliver similar parameter estimates. The proposed two-component model improves the in-sample diagnostics and generates more accurate out-of-sample forecasts.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Modelling volatility dependence with score copula models ; volume:27 ; number:5 ; year:2022 ; pages:649-668 ; extent:20
Studies in nonlinear dynamics and econometrics ; 27, Heft 5 (2022), 649-668 (gesamt 20)
- Urheber
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Alanya-Beltran, Willy
- DOI
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10.1515/snde-2022-0006
- URN
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urn:nbn:de:101:1-2023122113093906691796
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:35 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Alanya-Beltran, Willy