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Bayesiansk ARCH-modell×Bayesiansk TGARCH (Tröskel-GARCH med Bayesiansk estimering)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1982 (ARCH); 1989 (Bayesian estimation)1994 / 2008
UpphovspersonRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)
TypVolatility model with Bayesian inferenceVolatility model with asymmetric threshold and Bayesian inference
UrsprungskällaEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗
AliasBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHBayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B
Närliggande66
SammanfattningThe 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.Bayesian TGARCH combines the Threshold GARCH volatility model — which captures the asymmetric response of volatility to positive versus negative shocks — with full Bayesian inference via Markov Chain Monte Carlo sampling. The result is a principled, uncertainty-aware framework for modeling leverage effects and fat-tailed financial returns.
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ScholarGateJämför metoder: Bayesian ARCH model · Bayesian TGARCH. Hämtad 2026-06-15 från https://scholargate.app/sv/compare