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Model GARCH (Peramalan Volatilitas)×Regresi Kuantil×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal19861978
PencetusTim BollerslevKoenker & Bassett
TipeConditional volatility modelConditional quantile regression
Sumber perintisBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)conditional quantile regression, regression quantiles, Kantil Regresyon
Terkait55
RingkasanThe 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateBandingkan metode: GARCH Model · Quantile Regression. Diakses 2026-06-17 dari https://scholargate.app/id/compare