ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Fourier EGARCH: Modelització de la volatilitat amb canvis estructurals suaus×Autoregressiu Condicional Heteroscedàstic Generalitzat (GARCH)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen2010s1986
Autor originalExtension of Nelson (1991) EGARCH using Fourier approximation frameworksTim Bollerslev
TipusVolatility model with smooth structural breaksConditional volatility model
Font seminalEnders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗
ÀliesFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Relacionats35
ResumFourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number.GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 1 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: Fourier EGARCH · GARCH. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare