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Model GARCH (Peramalan Volatiliti)×Regresi Kuasa Dua Terkecil Biasa (OLS)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19862019
PengasasTim BollerslevWooldridge (textbook treatment); classical least squares
JenisConditional volatility modelLinear regression
Sumber perintisBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
AliasGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Berkaitan55
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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateBandingkan kaedah: GARCH Model · OLS Regression. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare