Regression modelEconometrics / time series

Nonlinear EGARCH Model

The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.

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Sources

  1. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI: 10.2307/2938260
  2. Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. Journal of Finance, 48(5), 1749–1778. DOI: 10.1111/j.1540-6261.1993.tb05127.x

Related methods

ScholarGateNonlinear EGARCH model (Nonlinear Exponential Generalized Autoregressive Conditional Heteroscedasticity Model). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/nonlinear-egarch-model