Short Term Stress of Covid-19 On World Major Stock Indices

The main objective of this study is to check short term stress of COVID-19 on the American, European, Asian, and Pacific stock market indices, furthermore, the correlation between all the stock markets during the pandemic. Secondary data of 41 stock exchange from 32 countries have been collected from investing.com website from 1st July 2019 to 14th May 2020 for the stock market and the COVID-19 data has been collected according to the first cases reported in the country, stocks market are classified either developed or emerging economy, further divided according to the subcontinent i.e. America, Europe, and Pacific/Asia, the main focus in the data is the report of first COVID-19 cases. The study reveals that there is volatility in the all the 41 stock market (American, Europe, Asia, and Pacific) after reporting of the first case and volatility increase with the increase of COVID-19 cases, moreover, there is a significant negative relationship between the number of COVID-19 cases and 41 major stock indices of American, Europe, Asia and Pacific, European subcontinent market found more effected from the COVID-19 than another subcontinent, there is Clustering effect of COVID-19 on all the stock market except American's stock market due to smart capital investing.

decreased seen in the employment rate, the number of business has been disabled nancially and numbers of business are awaited for the Government aids. Alfaro, L., Chari, A., Greenland, A. N., & Schott, P. K. (2020) researched the change in the market return due to COVID-19 and research shows that 4% to 11 % signi cantly decline has been seen in the total market value and further they nd that the increase in the number of cases causes a decrease in the volatility of the market returns. Zhang, D., Hu, M., & Ji, Q. (2020) research about the impact of COVID-19 on world nancial markets, they argue that the due to COVID-19 record level of risk increase in the market which affected the investors in very limited time. Onali, E. (2020) investigate the COVID-19 effect in term of the number of cases and deaths on US and Europe stock markets and results reveal that there is no impact of COVID-19 on the market returns of US Stock market also he nds that there is a negative relationship between COVID-19 cases and market returns of the Italy and France stock exchange. Nozawa, Y., & Qiu, Y. (2020) investigate the market reaction of the corporate bonds during the COVID-19 and they nd that the Central bank promised to support cut down the default risk for loan borrowers and further, the result shows mixed evidence about the market reactions caused by the market segments and liquidity channels. Ortmann, R., Pelster, M., & Wengerek, S. T. (2020) investigate the impact of COVID-19 outbreak on the retail investors, the ndings show that the signi cant increase has been seen in the stock trading while increase in the cases speci cally older age and male investors, 13.9 % trading in stock increased in the week which affects the stock index and 9.99% decline recorded in Dow 30 on 12 th March 2020.
Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020) investigate the impact of COVID-19 on world 21 major stock indices in short term, the results show that the word major stock markets have directly affected due to COVID-19 and signi cantly decreased after the COVID-19 outbreak has been recorded, moreover their results show that Asian countries are more affected than the other regions. Further, regression analyses reveal that there is a negative relationship between the increase in the number of cases and stock indices return. Çıtak, F., Bagci, B., Şahin, E. E., Hoş, S., & Sakinc, İ. (2020) investigate the effect of COVID-19 on the stock market they found that there is an existence of signi cant and negative impact of COVID-19 on the Stock market of all the countries. Heyden, K. J., & Heyden, T. (2020) investigate that what impact on the stock market of USA and European after the report of rst COVID-19 case in the country, the result shows that there is a negative relationship between the report of the rst case and the stock market, further they identify that the scal policy also negatively impacted on the stock market returns, improvement in the stock market has recorded after the announcement of monetary policy.

Research Methodology
Research Method states to technique is being used to perform research related to business; it offers a technique to the examined outcome for particular Challenge in Research Study intended for the whole study is conducting, it shows the path, road-map, combination, and sense for creating dependable results and create outcome bene cial for every stake-holders used for that study, a proper method can Create comprehensive outcomes or vice versa, that's why procedure retains the worth of core part in researches.
In this research the secondary data has been collected of 41 major stock markets indices from the 32 countries data has been collected from investing.com for stock indices from 1 st July 2019 to 14 th May 2020 and www.ourworldindata.org for COVID19 cases on daily basis from the period of reported the rst case of COVID19 according to the country till 14 th May 2020. The market has been classi ed into developed and the emerging market further we divided the data according to the subcontinent (Morgan Stanley Classi cation Index), below tables represents the classi cation of indices and countries. Deviation, and Relatives Ranking of each index, Median and Standard Deviation is calculated based on daily return and compressed to the monthly returns and then this monthly median and the standard deviation is used to assign relative rankings.
In the second segment, we quanti ed the Correlation matrix before and after the pandemic to see the international indexes joint movement to each other, is this segment we developed two matrixes and its analysis.
The third phase represents the impact of COVID-19 on indices return in the continent, for that we individually run regression model by using linear regression model using the daily basis data starting from the rst case reported of COVID-19 in the country to 14 th of May, 2020 and see constructed a comprehensive table which illustrates how each index is effect by the % change in Covid-19 cases by its coe cient and p-values.
Not only we set the regression for each index, but also we see the clustering effect in each index in phase four by using EGARCH model to use of daily basis data from 1 st July 2019 to 14 th May 2020 and see the clustering effect by dividing them into two broad categories as Developed and Emerging Market as per the guideline of MCSI. Now in the fth phase of the research, we constructed a single index by averaging daily returns of respective indices in two broad categories as Developed and Emerging Market, this time we tested the joint clustering effect on Developed and Emerging Markets by assigning it a single index through Averaging.
In the last segment phase 6 we use the same methodology as in step ve, but this time we jointly tested the clustering effects in all of the 4 sampled continents by using the EGARCH model. The following EGARCH model was assessed for the study.
3.1.6 Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) The equation above denotes the constant of the variance equation; is the βlog + (σ2t-1) GARCH term which evaluates the size of the group effect in the restricted volatility of the selected indices returns. α ⌊(Et-1)/(σt-1)⌋ is the ARCH term which measures the closeness and scope of ARCH in uence in the measured conditional uctuation. Is the asymmetric γ (Et-1)/(σt-1) expression which evaluates the vastness of asymmetric effect. Asymmetric term measures the size of the uneven effect in the restricted variations of the selected indices return. Adverse innovation, normally principals for the greatest part stimulates higher next period volatility distinguished with positive development. This component is known as Asymmetric impact (Ding et al., 1993). The purpose of keeping above mentioned statistic was to analyze the median shift in the returns of the each index, therefore not only we reported the shift in the median as well as encountered the risk associated with the return in term of standard deviation it has been measure, shift of median showcased that since Novel Covid-19 has not been declared as pandemic, the indexes above exhibiting the strong stability with steady risk associated, on 11 March Novel Covid-19 declared as pandemic by the World Health Organization (WHO), then stock market aggressively shown the abnormal change and huge shift in the average returns, we have target the indexes classi ed into American region, whereas the virus largely hit the world biggest economy so perceive consequences in term of stock markets could be seen into American stock market, therefore the shift of median from month to month trailing 11 months encountered in this research exhibited massive change each American index, Covid-19 declared pandemic outbreak in the month of March and the massive change have been detected into each American indexes, the best ranked index become eventually the worsen such as Dow 30, S&P 500, Nasdaq, SmallCap 2000 and S&P 500 VIX ranked 39, 42, 30, 36 and 43 in Mar20 (Jul-19, 17, 5, 3, 15 and 13) on basis of monthly median returns respectively, further we had ranked entire indices classi ed by the investing.com, hence S&P/TSX (Canada) and Hang Seng (Hong Kong) indexes were removed due to insu cient data of Covid-19, moving forward in term of standard deviation the highest ranked indexed best and vice versa, meaning indices with bigger rank number are consider best because risk associated with them are on very low level therefore comparing to this phenomena again American indexes reported the worsen ranked in term of risk, such as one to ve indexes shown the shift in risk 8, 11, 10, 2 and 1 in Mar20 (Jul-19 41, 38, 23, 19, 1) respectively. The information also claims, when Covid-19 cases shown signi cant increment in American ultimately put the impact on the American stock market and stood the stock market on the verge of collapse. Therefore the American stock market was classi ed as the highest vulnerable stock market around the globe. Not only there is a signi cant shift into the rank but also the aggressive shift has been observed into the American stock market within 5 months only especially in the month of March-2020 after declaration as a pandemic. Many articles classi ed Asian stock market as the least vulnerable market, hence this is being exhibited by the above-mentioned table, an aggressive is seen only in Chinese stock market and rest market reported steady risk and stable returns, going towards Chinese stock market which showcases the massive median shift in the month of February-2020 in each Chinese indexes, it is very interesting before pandemic declaration the Chinese market more vulnerable and later proclaimed the signi cant stability in term of Monthly Average Returns, Standard Deviation, Median and Standard Deviation ranks. The number indicates that when there is a massive change in the number of Covid-19 reported cases in January and February then the market lost its stability. Coming towards rest of the stock market into Asia, Indian stock market shows healthy improvement in term of average monthly returns and stable rank shift, not only Indian Stock market but also Pakistani stock market shows stability in the global pandemic because these are the countries which adopted smart lockdown policy and intended to run stock market as usual.  Panel 4 consists on Paci c and Gulf indexes, gulf region countries are least victim countries, business activities are impacted heavily due to coronavirus pandemic in the paci c region and the shift of abovementioned factors support the statement, the major shift into the factors is being seen in Nikkei 225

Results And Findings
(Japan) and STI Index (Singapore) in March. Nikkei 225 reports median average return -1.13% in Mar-20 (Jul-19 0.03%) and Median rank 35 in Mar-20 (Jul-19 20), however, STI Index exhibited monthly average return at -0.95% in Mar-20 (Jul-19 -0.07%) with ranking as 33 in Mar-20 (Jul-19 31), in term of ranks STI is not hit as much higher as Japan, the most considerable thing in the pandemic, according to survey Covid-19 attacks quickly on people who are above 40 years, hence a noticeable thing that Japan inherent skewed population in term of age group, there are more aged people compare to the teenage or young, further the people in an age of 30 to 35 are in established phase and they are potential investors, therefore it can be perceived that Japan's market was given hit due to withdrawal of potential aged investors.
We have taken the date before and after the pandemic, hence above mentioned correlation matrix are before Coronavirus cases, there are few indexes which have strongly signi cant correlation such as American and European indexes, therefore the purpose was to see the relationship of the global indexes to each other, hence in the second correlation matrix, we found very different results.
The European region is considered the most effective countries by Covid-19, above matrix, was constructed after the very rst case of Covid-19 till 14 of May 2020, therefore it is being witnessed that before pandemic the market was stable and have very least correlation but after the Coronavirus pandemic entire European capital market started to travel in the same direction highlighted as in red. As per the theory of Forbes and Rigobon (2002) the domino effect of one market to another one, if one market crashed in the same region then there many chances that it will affect some other market, and this what is seen in the correlation matrix after the very rst case of Covid-19 to the current date, the correlation markets indicates market to market impact in American & European regions, and these are the regions which are badly affected by the virus. * p-value > 0.05 but < 0.10 or > 5% and < 10% ** p-value > 0.01 but < 0.05 or > 1% and < 5% *** p-value < 0.01 or < 1% By using linear regression model, we quanti ed the relation of % change in Coronavirus cases to index returns, panel 1 consists on American indices, the indices from A to DI witnesses negative signi cant relationship between % change in cases to the index returns, as much higher the percentage as much will be a decline into the stock market, hence America is the highest affected region by Novel coronavirus and off course due to complete lockdown in the entire states of America brought signi cant decline into the capital market, many businesses closure and compressed of demand of basics products put the market in trouble, supporting to above statement these are the major indices in America which have potential represent entire American region collectively.
Panel 2 comprised on Asian region stock indexes, due to rapid increase in Covid-19 cases in China, Thailand and Philippine impacted heavily on the economy of these countries including the stock market as well, the outbreak took its rst breath in Wuhan (China Mainland) and travels from China to the entire world, therefore  We have excluded Russian RTSI (Russia) and Budapest SE (Hungary) from the rankings because Covid-19 has no impact on these indexes, we used coe cient to account for the minor and major change in the % change in cases bring the unit to change into index return, therefore above mentioned ranks allow us to pass comments that Austria is the highest in uential country in term of coe cient increment, suppose 1% changes are detected in % change of cases so it will bring 3.30% change into the stock market returns of ATX index, although Worldsdometer ranks Italy, Spain, Germany, and Turkey into to ten effected countries but above grid shows indeed a signi cant inverse relationship between % change in cases and index return the effect is very nominal.
Panel 4 is quanti ed on Paci c and Gulf-based indexes, S&P/ASX 200, STI Index and Tadawul All Share show a signi cant negative relationship between coronavirus cases and stock market returns, the coe cient of the equations are very low that means there is a very minor type of effect on the indexes by the increment in the Covid-19 cases within the country, therefore the relationship still exists and can't be ignored at all.  p-value > 0.05 but < 0.10 or > 5% and < 10% ** p-value > 0.01 but < 0.05 or > 1% and < 5% *** p-value < 0.01 or < 1% Not only we detected the effect and intensity of the Covid-19 on stock indices but also we have encountered clustering effects into each index classi ed as Developed and Emerging markets, to measure volatility in the stock indices we have used ordinary least square (OLS), GARCH, TARCH, PARCH and EGARCH models, as per the information criterions (AIC, HIC, and HQC) the least valuable one model is the best, we have selected to used EGARCH model in both of the panels, we have tested every single index to nd the clustering effect in the markets by using dummy in place of reported cases on daily basis, below is the list of cumulative cases on the last terminal day of this research. It has discussed previously, America found the highest affect country around the globe; around 1.3m cases are reported in US and New Zealand as the least cases around the world. Anyhow, according to above mentioned EGARCH equation witnessed the smart policies of Portugal and Australia because the PSI 20 & S&P/ASX 200 asymmetry term is insigni cant, which indicates that in both of the indexes there is no instable uctuation which harms market decorum, therefore it is also noticeable that these both market are saved from markets shocks generated by the bad news. Coming towards the rest of the indices, almost every index reported the clustering effects because p-value of the EGARCH Term is under accepted regions, meaning we cannot reject the alternative hypothesis, there are clustering effect in the model, meaning period of low volatility is followed by period of low volatility for prolonged period and period of high volatility is followed by period of high volatility, if one day return is negative then there possibilities that next will be negative too and this pattern remains same with a certain time, and what has been seen in the rest of the indexes in developed market. It is also noticeable that most of the indexes categorized into the developed market are from America or Europe and that is the red zone area of Covid-19, since it is declared a global pandemic entire markets shows negatives returns mentioned by the model above.   In every individual phase of this research paper, we found European market is the most affected market by the Covid-19 and most of the indexes are in the developed market comes under European region, therefore we needed to hypothesize the Covid-19 clustering effect on Developed and Emerging Market collectively, before this segment we analysis the market on an individual basis by using regression and EGARCH Model, but in this segment, we have averaged out the daily return of each index and plugged this into the respective category and created single indexes for developed and emerging markets.
Initially, we tested the ARCH effect in the both constructed equation and found ARCH effect because pvalue of AR (1)   See Figure 4 uploaded in gure section.
To drive result for Asian Stock market we use the same pattern of calculating index and regressed it for EGARCH model as above, initially we applied the ARCH test to see whether long term volatility is followed by another period of long term volatility or in easy words can ARCH family models be used to witness clustering effect into the region, hence the test allowed us to use ARCH family models, we found EGARCH model is the best-suited model, Asian markets reported the negative abnormal returns, meaning as Covid-19 cases increases in the market produce the negative downwards, going forward it has also been noticed that market has strong clustering effect in the pandemic period. According to worlddometer and rest of the other authentic sources, Asia is the least affected region by Covid-19 (Apart from China), two factors became the cause of cushion or savior for Market from the virus effect, (1) Smart LockDown in the Market and (2) Rapid Recoveries from the Virus, further, we can't ignore the role of cumulative cases in Asia which still lesser than rest of the other regions, and we found the least volatility into the market.
We employed the ARCH-LM test to check model tness and the p-value is less than more than 0.05 or 5% which further indicates there is no ARCH type of effect in the model and model is t to use for prediction.
Below is the graph which illustrates % of Covid-19 cases in the pandemic.
See Figure 5 uploaded in gure section.
America is considered second the highest affected region by Covid-19, interestingly we could not nd clustering effect into American stock market, by using the same methodology as above we employed the EGARCH model and found indeed there is a signi cant relationship between individual American Index and Covid-19 cases, but there is no clustering effect as illustrated by the value of the Asymmetry term market is not effect by the negative shock or news in the pandemic, in the light of the above numbers we can claim that America uses good Standard Operating Procedure (SOPs) to stabilize the capital market in America. ARCH-LM test de nes the model tness because p-value is more than 0.05 or 5%, further below is the graph of % of Covid-19 cases in the American Countries.
See Figure 6 uploaded in gure section.
We have also constructed model with continent indexed daily average returns with cumulative cases in the continent and also with dummy variable by replacing cumulative cases into EGARCH model, employed data is divided into categories (1) before the Covid-19 cases not a single case reported in the region (we use 0 as dummy variable) and (2) After the very rst cases Covid-19 (we use 1 as dummy variable). We found the rst model not suitable because nding were against logics so we dropped that model and decided to select the second model with the dummy variable and the model is with the logic and realities.

Discussions And Conclusion
5.1 Discussion: the purpose of this study is to encounter Covid-19 impact on global indices; hence we have selected the best performing indices around the globe classi ed by the investing.com, we have used umbrella approach to see market movement before and after pandemic by using different models, in the rst phase of the research we used descriptive statistics by classifying it region-wise as per the methodology of MSCI, in which we see the median shift, standard deviation shift and relative rank shifts before and after the pandemic, plus also try to relate the cumulative cases with these shifts into each sampled index. In the second phase, we have seen the correlation matrix where is used to see the joint movement of entire sampled indexes to each other before and after the pandemic, in the third phase we tested linear regression model for each index by categorizing them region-wise as per the MCSI classi cation to see the impact of % change into Covid-19 with single individual index, not only the impact of Covid-19 to index return we also encountered the clustering effect-Volatility in each index by using EGARCH model in this is classi ed as Developed and Emerging Market as per the methodology of MSCI this is in phase four. With the same method by dividing markets into two broad segments as Developed and Emerging Market, we collectively tested clustering effect by using EGARCH model in phase ve, in the last phase six we classi ed the indexes into four broad categories as America, Asia, Europe, and Paci c & Gulf by assigning them a single index and constructed variance equation by using EGARCH model.

Conclusion
: as per international reports, articles and other authentic source, region Europe found the highest affected region around the globe, hence our research found the European Market in much vulnerable and risk, shifts in descriptive statics shown the trend how European market goes from better to good and worse nally, in these 11 months shifts indicates not only returns are affected by the Covid-19 in European capital market but also ranking with peer group became worsen, further the correlation matrix illustrated after the rapid increase in the Novel Coronavirus Cases entire European market exhibited highly correlated market, means almost all big indexes in Europe move closely to each other and the linear regression model supported the this movement by illustrating the signi cant impact on the Market Returns, moreover in MSCI index classi cation most indexes in Developed Market are from European countries, due to this Developed ARCH model reported clustering effect in the developed markets, and nally in the last model we have found European Market has the highest volatility in relation to Covid-19.
With the rapid increase of Covid-19 cases in America affected American indexes, we found that American indexes exhibited signi cant shifts in term of average monthly returns, standard deviation, and relative rankings before and after the announcement of the pandemic by World Health Organization, we found American Indices as stable because of intellectual and smart investment policies for capital markets, indeed there is a signi cant and strong impact of Covid-19 on indices returns but no evidence found for clustering effect/volatility in American indices.
Paci c & Gulf region countries reported the third-highest Covid-19 cases, therefore we found the great shift in medians, standard deviation and relatives ranking in Paci c & Gulf indices, further we also detected Covid-19 impacts on indexes daily returns, therefore in the last segment we found the Paci c & Gulf indexes are classi ed as the second highest volatile market having strong clustering effect in contrast to Covid-19 cases.
Due to fewer cases reported in the Asian region and smart lockdown policy, we found that Asian stock index indeed has Covid-19 impact on indexes but least clustering effect compare to Europe and Paci c & Gulf, median shift indicated that after the declaration of pandemic (11-March-2020) market reported a signi cant change in each index on Asian capital Market, therefore we can conclude Asian Capital Market has the third effect market by the Covid-19.

Declarations
It has been declared that there is no con ict of interest any of the authors