GJR-GARCH(1,1)

The 'GJR-GARCH(1,1)' model is a statistical model used to evaluate the volatility of financial time series data, particularly capturing the effects of asymmetry in volatility and allowing for time-varying conditional variances.

Papers using GJR-GARCH(1,1) (1)

Deep Reinforcement Learning Algorithms for Option Hedging2025