Modeling the volatility of Banks index returns for the Saudi stock exchange using EGARCH model

This study aims to model and measures the volatility of the returns of the banking sector in the Saudi stock exchange. The study used the exponential generalized autoregressive conditional heteroskedastic (EGARCH) model. The banking sector index (TBNI), comprises of daily data from the period from 1st April 2019 to 30st April 2020. Asymmetry presence has been detected in the EGARCH model. A using a Generalized Error Distribution was the most appropriate for the model. Besides, we found that “ bad news ” tends to increase volatility in comparison with “ good news ”, because the world is going through a corona epidemic