Investigating the impact of COVID-19 pandemic on volatility patterns and its global implication for textile industry: An empirical case study for Shanghai Stock Exchange of China

Abstract

This research paper aims to examine the impact of the COVID-19 pandemic on volatility patterns and its global implication for the textile industry in China. The COVID-19 pandemic has generated a global health crisis with profound economic, social and financial implications, but also has triggered a ruthless global recession. The global economic recovery as a result of the COVID-19 pandemic can also generate significant investment opportunities for the textile industry in China. In this paper, the application of empirical methods could explain historical prices, the movement dynamics of financial assets, and investigate various important characteristics of asset pricing that explore details of the Chinese stock market. The econometric framework includes the following: symmetric Generalize Autoregressive Conditional Heteroscedastic GARCH (1, 1) model, asymmetric GARCH models such as EGARCH and GJR models. The main aim is to identify the asymmetric volatility effect, and impact of news on the SSE Composite Index and investigate long memory properties in volatility using daily data for the sample period from 19th December 1990 to 31st December 2020. This empirical study contributes to the existing literature on the impact of the COVID-19 pandemic on international stock markets, by investigating symmetric and asymmetric volatility patterns in the case of the Shanghai Stock Exchange from China.