Analysis of Saudi stock market volatility by using ARMA and GARCH Models during COVID-19 pandemic
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Abstract
Currently, global markets are in a state of instability and turmoil because of the impact of the
COVID-19 pandemic, and it has pushed governments all over the world to take emergency
actions to protect their people and economy. This study aims to fill the gaps in the analysis of
the performance and model the return volatility of TASI in the Saudi market during the
COVID-19 pandemic. The study employs the linked time series models identified through a
literature review. It uses different autoregressive models such as ARMA and GARCH family
models for forecasting. The analysis includes data on daily prices of TASI for the period
between January 1, 2015, and June 30, 2020.
The study used the information criteria of the SBIC to assess the best models describing the
volatility of returns during the selected period while accurately forecasting the true volatility
of autoregressive models based on RMSE and MAE equations. The results show that TASI
index does not get affected much by an increase in the number of COVID-19 cases in Saudi
Arabia because of the economic support provided by the government. Moreover, the ARMA
(1,1) model is the best in terms of describing the return volatility. However, when RMSE and
MAE were used. It was found that TGARH (1,1) and GARCH (2,2) models are the most
appropriate models for the forecast of volatility.