Stock return volatility during SARS and COVID-19: Comparison between Malaysia and China's stock markets

• Published in: AIP conference proceedings 2022-08, Vol.2472 (1)
• Main Authors: Hamzah, Siti Raihana, Azhar, Azah Syafinaz, Ishak, Norizarina, Raseedee, Ahmad Fadly Nurullah
• Format: Article
• Language: English
• Subjects: Autoregressive models; Coronaviruses; COVID-19; Pandemics; Root-mean-square errors; Securities markets; Stochastic models; Stock exchanges; Volatility
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0092822

This study analyses return volatility for Malaysia and China's stock markets during the SARS and COVID-19 pandemics. Stock return volatility is estimated using GARCH family models (GARCH (1,1), TGARCH and EGARCH). Generally, GARCH (1,1) estimates symmetric conditions, whereas TGARCH and EGARCH estimate the asymmetric condition or leverage effect of return volatility. Stock return volatility in China and Malaysia are then compared to assess the severity of pandemic cases during the study period. Post pandemic, Malaysia is seen to experience higher decrements in leverage effect when using the TGARCH model. Conversely, the effect is higher for China when using the EGARCH model for the SARS pandemic. To aid in predicting future return volatility after the COVID-19 pandemic, return volatility after the SARS pandemic is forecast, with the forecast value serving as the basis for evaluating the error using the mean absolute error (MAE), root mean square error (RMSE) and Theil inequality coefficient (TIC) approaches. The forecast error performance is ranked to identify outperforming GARCH family models for the pandemic period: the TGARCH model for China's stock market but the GARCH model for Malaysia's stock market.