This paper aims to propose the augmented GJR-GARCH (GJR-GARCH<sub>M</sub>) model that extends the GJR-GARCH model by comprising overnight returns volatility (ONV), daily high-low prices range (PK), and fear index (VIX) as explanatory variables for the GJR’s variance equation, respectively. The proposed models are used to estimate the daily value-at-risk values and evaluate their downside risk management performance for the SPDRs covering the period from 2009 to 2014. Empirical results show that the GJR-GARCH<sub>M</sub> model outperforms the GJR-GARCH model for most cases, suggesting that the GJR-GARCH-based VaR forecasts can be moderately improved with the additional information embodied in the ONV, PK and VIX volatility estimators. In addition, daily high-low prices range and VIX are far more informative than the overnight volatility estimator for improving the GJR-GARCH-based VaR forecasts. Risk managers can employ the proposed models for estimating and controling the potential loss of ETFs in the face of financial catastrophes.
VIX (Korku Endeksi) ile BİST Endeksleri Arasındaki Volatilite Etkileşiminin DCC-GARCH Modeliyle Analizi(Analysis of Volatility Interaction Between VIX (Fear Index) and BIST Indexes With DCC-GARCH Model)
