Porovnať metódy

	Model GARCH (predikcia volatility)	Regresia metódou najmenších štvorcov (OLS)
Odbor	Ekonometria	Ekonometria
Rodina	Regression model	Regression model
Rok vzniku	1986	2019
Tvorca	Tim Bollerslev	Wooldridge (textbook treatment); classical least squares
Typ	Conditional volatility model	Linear regression
Pôvodný zdroj	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
Ďalšie názvy	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Príbuzné	5	5
Zhrnutie	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).