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Bayesian ARCH-Modell×ARCH-Modell (Autoregressive Conditional Heteroskedasticity)×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr1982 (ARCH); 1989 (Bayesian estimation)1982
UrheberRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Robert F. Engle
TypVolatility model with Bayesian inferenceConditional volatility model
Wegweisende QuelleEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
AliasnamenBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Verwandt66
ZusammenfassungThe 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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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ScholarGateMethoden vergleichen: Bayesian ARCH model · ARCH model. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare