Regression modelEconometrics / time series

Nelinearni GARCH model

Nelinearni GARCH model proširuje standardni GARCH okvir kako bi obuhvatio asimetrične i nelinearne odgovore uslovne volatilnosti na prošle šokove. On dozvoljava negativnim prinosima (loše vesti) da pojačaju volatilnost više nego pozitivni prinosi jednake magnitude, što je fenomen poznat kao efekat poluge, koji je empirijski rasprostranjen na finansijskim tržištima.

Primenite uz EconMindUskoroVideoUskoroDownload slides

Pročitajte celu metodu

Samo za članove

Prijavite se besplatnim nalogom da biste pročitali ovaj odeljak.

Prijavite se

Method map

The neighbourhood of related methods — select a node to explore.

Izvori

  1. Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779-1801. DOI: 10.1111/j.1540-6261.1993.tb05128.x
  2. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347-370. DOI: 10.2307/2938260

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Nonlinear Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/sr/econometrics/nonlinear-garch-model

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateNonlinear GARCH model (Nonlinear Generalized Autoregressive Conditional Heteroscedasticity Model). Preuzeto 2026-06-15 sa https://scholargate.app/sr/econometrics/nonlinear-garch-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026