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

Modelul Bayesian ARCH×Model GARCH (Prognoza volatilității)×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției1982 (ARCH); 1989 (Bayesian estimation)1986
Autorul originalRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Tim Bollerslev
TipVolatility model with Bayesian inferenceConditional volatility model
Sursa seminalăEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Denumiri alternativeBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Înrudite65
RezumatThe Bayesian ARCH model estimates Engle's Autoregressive Conditional Heteroskedasticity specification within a Bayesian framework. Instead of maximising a likelihood, it combines a prior distribution over the volatility parameters with the data likelihood to obtain a full posterior distribution, providing richer uncertainty quantification than classical maximum-likelihood ARCH.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
  1. v1
  2. 2 Surse
  3. PUBLISHED
  1. v1
  2. 1 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Bayesian ARCH model · GARCH Model. Preluat la 2026-06-15 de pe https://scholargate.app/ro/compare