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Autoregressiu Condicional Heteroscedàstic Generalitzat (GARCH)×Regressió per Mínims Quadrats Ordinàris (MQO)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen19862019
Autor originalTim BollerslevWooldridge (textbook treatment); classical least squares
TipusConditional volatility modelLinear regression
Font seminalBollerslev, 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
ÀliesGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionats55
ResumGARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.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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