Compara mètodes

	Model GARCH (Previsió de la Volatilitat)	Regressió per Mínims Quadrats Ordinàris (MQO)
Camp	Econometria	Econometria
Família	Regression model	Regression model
Any d'origen	1986	2019
Autor original	Tim Bollerslev	Wooldridge (textbook treatment); classical least squares
Tipus	Conditional volatility model	Linear regression
Font seminal	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Àlies	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionats	5	5
Resum	The 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).