ScholarGate
Pembantu
Regression modelEconometrics / time series

Model EGARCH Teguh

EGARCH Teguh melanjutkan model EGARCH Eksponensial Nelson (1991) dengan menggantikan anggaran kuasi-kemaksimum kebarangkalian standard dengan prosedur tahan pencilan — biasanya pengaruh terhad atau anggaran-M — supaya sebahagian kecil pemerhatian ekstrem atau kesilapan data tidak dapat mendistorsi dinamik volatiliti yang dianggar atau kesan ungkit.

Terapkan dengan EconMindTidak lama lagiVideoTidak lama lagiDownload slides

Baca kaedah sepenuhnya

Ahli sahaja

Log masuk dengan akaun percuma untuk membaca bahagian ini.

Log masuk

Method map

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

Sumber

  1. Muler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940. DOI: 10.1016/j.jspi.2007.11.003
  2. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI: 10.2307/2938260

Cara memetik halaman ini

ScholarGate. (2026, June 3). Robust Exponential Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/ms/econometrics/robust-egarch

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

Dirujuk oleh

ScholarGateRobust EGARCH (Robust Exponential Generalized Autoregressive Conditional Heteroscedasticity Model). Dicapai 2026-06-15 daripada https://scholargate.app/ms/econometrics/robust-egarch · Set data: https://doi.org/10.5281/zenodo.20539026