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Tidsvarierende Parameter DCC-GARCH Modell

TVP-DCC-GARCH-modellen utvider Dynamic Conditional Correlation GARCH-rammeverket ved å tillate at ikke bare de parvise korrelasjonene, men også de underliggende modellparametrene, utvikler seg kontinuerlig over tid. Den fanger opp strukturelle skift i volatilitetsdynamikk og kryss-aktiva-avhengighet, noe som gjør den essensiell for finansiell risikomodellering i ikke-stasjonære miljøer.

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  1. Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI: 10.1198/073500102288618487
  2. Christoffersen, P., Errunza, V., Jacobs, K., & Langlois, H. (2012). Is the potential for international diversification disappearing? A dynamic copula approach. Review of Financial Studies, 25(12), 3711-3751. DOI: 10.1093/rfs/hhs104

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ScholarGate. (2026, June 3). Time-Varying Parameter Dynamic Conditional Correlation GARCH Model. ScholarGate. https://scholargate.app/no/econometrics/time-varying-parameter-dcc-garch-model

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ScholarGateTime-varying parameter DCC-GARCH model (Time-Varying Parameter Dynamic Conditional Correlation GARCH Model). Hentet 2026-06-15 fra https://scholargate.app/no/econometrics/time-varying-parameter-dcc-garch-model · Datasett: https://doi.org/10.5281/zenodo.20539026