Understanding the Impact of COVID-19 on the Volatility Dynamism of Brics Stock Market

The current study is aimed at examining the impact of COVID-19 on the volatility of stock market returns in the BRICS economies known as trading partners. Due to the pandemic situation all over the world, it had influence on the working of the stock markets as the investors were vigilant of their investment position. Since the World Bank declared the first confirmed case of covid-19 on 31 st December 2019, hence the daily data of the stock indices of the each of the BRICS economies has been fetch ranging from 1 st January 2020 to 31 st march2021. The impact of Covid-19 has been studied by taking the number of daily Covid-19 cases in the respective economies. The study employed GARCH family of models such as GARCH(1,1), EGARCH(1,1) and MGARCH(1,1) in order to understand the nature and dynamics of volatility of the stock markets of BRICS economies so that investors can make decisions regarding portfolio management while investing in such economies acting as global trading partners. The study found that except China and South Africa, the rising number of cases has significant impact on BRICS economies volatility. The level of persistence is found to be high, revealing that it takes time to volatility to wipe out from the market, indicating that the BRICS stock market remained volatile for a longer period of time due to the arrival of Covid news.


Introduction
Investors around the globe are cautious of their investment position due to sudden eruption of the covid19 news in the stock markets. The stock market reacts quickly to any information or news that has tendency to affect the sentiments of the market in a positive or negative manner. The outbreak of disease and thereby the spread of number of increased cases created an alarming situation among the stock markets of the world. The decline in the stock market returns was more severe during 40-60 days of the news of spread of virus (Ashraf, 2020). The one-third of the economies around the globe had to face partial or full lockdown of economic activities (Hoof, 2020). Investors react quickly to the negative news as compared to the positive news. The arrival of Covid-19 and the sudden announcements of the lockdowns of various economic activities created a turmoil situation in the financial world. This was followed by the immediate measures taken by the governments of the nations including imposing restrictions on travel, guiding measures for social distancing, lockdowns, restricted economic activities such as only bare essentials services were allowed to operate. This led to the reduction in the movements of goods and people thereby curbing trade and activities. World bank declared Covid-19 as pandemic on March12, 2020. This announcement came as havoc in the stock market. This greatly impacted the world economy. (BBC news, 2020). This led to increase in volatility of returns in the asset prices. Volatility refers to the dynamic nature of the returns to change suddenly due to any news, information or event. The stock markets had to see unprecedented changes owing to Covid-19 (Zhang,2020). Owing to the arrival of third wave of Covid-19 in Japan and the consequent restrictions on business activities, it had impact on the consecutive falling down of stocks in Japan. As a repercussion, the economy of Japan saw a highest fall of 20% in stock prices on feb2020 as compared with the December 2019 period.US too noticed a turmoil situation when within a week; the stock market had to apply the circuit breaker in order to correct the price mechanisms in about four events. BRICS economies too had unexpected movements. On 12 th march, 2020, the price of FTSE index fell down for more than 10% since 1987(BBC, 2020). The Russian financial market too had to declare march 10 th , 2020 as black Monday, following which the share prices of Russian firms crashed by 20% (the Moscow Times, 2020). Although most of the stock markets have tend to follow the route of recovering, still the uncertainty hovers over the stock markets until the pandemic stays.
The current study holds importance due to several reasons. Firstly, the study endeavours to understand the volatility of BRICS stock market by increasing the time span as compared with previous studies having short time span. Secondly, very few studies exist to bring into light the comprehensive view of dynamics of volatility such as size & sign effect of the news, level of persistence and impact of shock using GARCH extension models. Also this study attempts to understand contribution of the variance in affecting the total returns in the BRICS stock market. High return spikes have been observed during the arrival of the news of the COVID in the BRICS economies. In case of China, the turmoil situation in the stock market has been observed at first during January,2020 among the BRICS economies, as China saw the first mark of Covid-19 virus. After china, an increased volatility of returns has been seen during feb2020 in Brazil, Russia, South Africa. Amongst all, India saw the increase in return spikes in march2020 due to rise in the number of cases. Negative lowest spikes have been observed on 27 th feb as this day marked the biggest fall in Dow Jones Industrial average when the fear of spread of Covid -19 increased outside china. On 12 th march also, negative returns have been observed in the stock markets as WHO acknowledged the pandemic on 11 th march 2020. On 30 th January 2020, marked as the event date of declaration of Covid-19 as public health emergency (Rahman et al. 2020). This led to multiple drops in world's stock market.

Review of literature
The research world is full of investigations concerning the influence of Covid-19 on the functioning of stock markets in recent months. Some of the studies focussed on evaluating the impact of rise in number of Covid 19 cases, impact of arrival of Covid news as pandemic, calibrated lockdowns, announcement of policy changes to curb the spread restricting economic activities of the countries. These have bearing on the functioning of financial markets. Some of the past studies on volatility dynamisms conducted in several nations are as follows.  Thus, Previous studies highlighted the impact of Covid 19 and incidental negative news such as announcement of lockdown, major policy changes on the stock indices of the nations among the world such as financial and non-financial firms, firms with large and small capitalisations. The current study attempts to measure the impact of Covid 19 on the emerging economies acting as a trading partner like BRICS taken individually.

Research methodology
BRICS equity returns has been taken from the equity indices of the respective nations. The daily returns of the indices of the BRICS stock market has been calculated with the natural log method. Since the World Bank confirmed first Covid-19 case on 31 st decemeber2019, hence the study ranges from 1 st jan2020 to 31 st march 2021. The study employed ARCH and GARCH family of models. The ARCH model has been developed by Engle in the year 1982 so as to forecast the volatility of the market. In linear regression model, it is presumed that variance in the error term is unconditional i.e not based on any past values, hence stated as variance is constant. But in ARCH model, the variance is assumed to be conditional or based on past values i.e up to previous period. Thus conditional variance is a function of past error terms. The daily number of Covid-19 cases from respective nations has been used as variance regressor to measure the impact of rising cases on the dynamics of volatility of returns. GARCH model developed by Bollerslev based on the assumption that the number of lagged square error required to notice the conditional variance may be huge in numbers. This study has further applied GARCH extensions such as EGARH(1,1) and MGARCH(1,1). EGARCH(1,1) has been employed in order to check for leverage effect in the returns data. MGARCH(1,1) has been used in order to examine the feedback relationship between conditional variance and conditional mean.

Objectives:
1. To study the impact of rising number of Covid-19 cases on the volatility of stock market of BRICS economies. 2. To analyse the volatility of returns with respect to conditional, persistence and news sensitivity during Covid-19. 3. To examine the asymmetric volatility with respect to size effect and sign effect of returns during Covid-19. 4. To examine the feedback relationship between conditional return and conditional volatility during Covid-19. The summary statistics shows that the highest mean daily return has been showed by India i.e 0.000840, followed by South Africa having mean return of 0.000580 and china as 0.000436 while the Russian stock market has shown lowest mean return. The stock market of Brazil is highly volatile (0.028%) followed by Russia(0.025%), India ( 0.0197%), South Africa ( 0.0190%) and china showing least volatility(0.013%). The stock returns data shows the maximum variations in the returns are found to the left side of the data hence all the returns are negatively skewed. The basic features of financial time series data is confirmed by summary statistics. In order to run ARCH models, the ADF test has been conducted in the returns series. ADF test confirms the mean reverting behaviour of the time series data. Further conditional mean equation has been generated after confirming for the stationary of the data. The fitness of the mean equation has been checked by analysing correlogram Q stat and the squared residuals from the series. The mean equation following the Auto Regressive Moving Average (ARMA) model has been shown below:

Analysis and interpretation
where Rt is indicative of the returns from specific index, and is error component. The above mean equation has been derived using Akaike information criterion (AIC) in order to determine the optimum lag length The above statistics found the trace of ARCH effects. The presence of volatility clustering is a must to apply GARCH models. The data shows the clustering of volatility indicating the circumstances that during the Covid, the highly volatile period is accompanied by the period of increasing volatility whereas the low volatile periods go along with less volatile periods. GARCH(-1) CASES_SOUTH_AFRICA The above results confirmed the significant impact of rising Covid19 cases on the volatility of returns in case of Brazil, Russia and India, while China and South Africa have insignificant impact of rising cases. The significant ARCH term is indicative of the nature of volatility due to shock, news and any significant information where as significant GARCH represents the nature of volatility as a tendency to remain persistent in the market. China emerged as the focal point of pandemic which moved to Europe and then to US. Insignificant impact of rising cases has been observed in case of china, this is due to the fact that china on account of resilient infrastructure, had been able to muddle through with the undesirable shock of Covid 19, while the global markets had to face a plunge in the later stage of pandemic (He et al. 2020 andAli et al. 2020). Insignificant impact has been confirmed in case of South Africa, according to WHO 1 , the African region observed the least number of Covid cases as compared with other regions of world.

EGARCH(1,1) Model
The exponential GARCH Model has been developed by Nelson in the year 1991 to understand the difference between the symmetric and asymmetric impact of positive and negative news. According to EGARCH model, volatility is asymmetric in nature, which reveals the unequal consequences of positive and negative sensitive information to create sensation in the market. Similar evidences have been showed by Ekong &Onye, 2017 andMagweva &Sibanda, 2020. As a technique, EGARCH also allows for the examination of the presence of leverage effects, stating that negative information leads to turmoil in the market more as compared with positive information.

Conclusion:
The purpose of the study was to highlight the Volatility dynamisms of the stock returns in case of BRICS economies and the impact caused by Covid 19. The study found that except China and South Africa, the rising number of Covid 19 cases has significant impact on BRICS economies volatility. Also the sign effect confirms the presence of volatility due to negative news in the market generates more turmoil situation as compared to positive one in the BRICS economies. The level of persistence is found to be high, revealing that it takes time to volatility to wipe out from the market, indicating that the BRICS stock market remained volatile for a longer period of time due to the arrival of Covid news.

Implications of the research:-
The current research will help the investors to acknowledge the pattern of volatility dynamisms of BRICS stock market. BRICS nations emerged as significant global trading partners. Any change in the stock markets of the BRICS nations has bearing on other nations of the world too. The study confirms the trace of leverage effects in the BRICS stock market during Covid period. So the investors should be cautious when they see the arrival of negative information or news in the market. Also the insignificant feedback relationship between variance and the returns confirms that higher the volatility higher the returns do not hold appropriate for the BRICS economies except Brazil. This study has implications while making portfolio investment decisions. The current research will guide the investors to incorporate Var (value at Risk) decisions persistent to the level of risk return in the context of portfolio diversification.