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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Modelul Arh Nonliniar (NARCH)×Model GARCH (Prognoza volatilității)×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției19921986
Autorul originalHiggins & BeraTim Bollerslev
TipVolatility modelConditional volatility model
Sursa seminalăHiggins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Denumiri alternativeNARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Înrudite45
RezumatThe Nonlinear ARCH (NARCH) model, introduced by Higgins and Bera (1992), extends Engle's original ARCH framework by allowing the power transformation of volatility to be estimated from the data rather than fixed at two. This flexibility captures a broader class of volatility dynamics observed in financial and macroeconomic time series.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
ScholarGateSet de date
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  2. 2 Surse
  3. PUBLISHED
  1. v1
  2. 1 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Nonlinear ARCH model · GARCH Model. Preluat la 2026-06-17 de pe https://scholargate.app/ro/compare