US and China pharmaceutical sector reaction to the COVID-19 pandemic

. This study investigates the performance of pharmaceutical stocks in China and the United States, considering the changes in composite market index, market volatility and economic policy uncertainty. Volatility has been intensified in both markets. During two periods, before and in COVID time, the Chinese pharmaceutical sector mainly performs in connection with overall markets, and volatility from the EU stock market contributes sector changes during the COVID period, while the US sector exhibits a positive correlation with market volatility during the pandemic. Policy uncertainty is not a significant factor in markets within the COVID window. An asymmetric effect is found in both markets during the pandemic. The study’s findings provide investors, policy-makers' information to adopt effective strategies under different market situations in future public emergencies.


Introduction
At the end of 2019, an unprecedented pandemic began in Wuhan, China in a way that triggered systemic and global human disaster.Since the confirmation by the World Health Organisation (WHO) on 11 March, 2020, of COVID-19 as a global pandemic, it has consumed 6,022,047 lives around the world.The global economy has been affected to different extents in the crisis.As the barometer of the market economy, stock market performance has been affected severely.For instance, the volatility index (VIX), designed by the Chicago option exchange, which measures the expectation of volatility in the US.stock market, based on Standard and Poor's 500 index option, rocketed to 82 on the 16 March, 2020, from an average level of around 15 [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17].
The urgent call for a COVID-19 solution has pushed the pharmaceutical industry into the spotlight.Unlimited population growth and human activities have put enormous pressure on ecosystems over the past few decades, and climate change, with the frequent emergence of infectious diseases, are the consequences of these actions [1].According to Torreya's analysis in 2021, the interest of the global capital market in the pharmaceutical industry has reached 7.03 trillion dollars from 1.99 trillion dollars since 2003.The COVID-19 outbreak is an accelerator to global pharmaceutical development.In the wave of the pandemic, top vaccine companies' stocks have soared to an unprecedented level.Table 1 provides stock prices from the top pharmaceutical companies in the world, Moderna's stock price is 7 times higher than it was in the pre-pandemic area (17$ per share), after reaching a peak of 22 times the pre-pandemic price in September 2021.Pfizer and AstraZeneca are also taking the lead in the vaccine development, this being reflected by their stock prices to varying degrees.MERCK & CO. still had a small rise.It is not hard to conclude that the pandemic has accelerated the global demand for pharmaceutical science and technology.
On the other hand, the ageing society has also continued to be the driving force behind the continuing growth of the healthcare industry including pharmaceutical industry, because our immune system's response to the outside world will be weaken, and peoples' need for medical care generally rises with age.By 2050, 20% of the global population will be aged over 60, and ageing population will stimulate massive healthcare innovation in the coming decades.Since the United States entered an ageing society in the 1940s, medical insurance and aid funds have been long accounted for a larger share of fiscal expenditure.According to the World Bank data (See fig.1), China accounts for nearly 23% of the world's population aged 65 and over and will undoubtedly have the largest elderly population in the future, while the growth rate of both country is close to 4% per year in 2020.An understanding of the role of the pharmaceutical industry in markets could inform public health decision-making.Source: Refinitiv To a certain extent, R&D expenses reflect the market and government's attention to a certain industry.According to the Pharmaprojects®, 2021 report (see fig. 2), the US is holding most biotech development activities, 46% of companies have headquarters in the US.The US leads the world in the field of biotech industry, by its long-term, unremitting huge financial investment and rich knowledge reserve, and its R & D investment accounts for about half of the total R & D expenses in the global market.Meanwhile, it is worth seeing that China has become the second largest pharmaceutical market.In the past 6 years, its market value share has grown from 6.5% to 12%, to a total value of 840,261million dollars in 2021.The quick spread of COVID-19 partly explains the rapid development in the Chinese pharmaceutical industry during the pandemic, and in recent years, the Chinese government has increased policy support for its pharmaceutical industry.Some peculiarities of the Chinese and the USA pharmaceutical markets exist: First, both countries' markets are fundamentally different, in terms of the conditions for the functioning of pharmaceutical enterprises, with differences in regulatory requirements for launching new products on the market.For this reason, progress in cutting-edge drug research and development progresses much faster in Asia compared to traditional US markets and Europe.In the Asian market, new drugs appear in much shorter terms, while in the West, companies have to wait for a long time for clinical trials results.
Second, countries ranked in the global pharmaceutical market have qualitatively different niches.China is the main supplier of primary raw materials, substances, APIs for the production of generics and brand drugs (20% of global volume), personal protective equipment (more than 40% world volume) and China covers more than 20% of global exports of generic medicines.The US and the EU are the main producers of final prescription drugs and brand drugs.
Third, technological separation explains the different responses of countries to the pandemic and differences in government responses in economic policy.
The main challenge of COVID-19 for the US pharmaceutical industry is the risk technological dependence of production on the situation in China (i.e., the risk supply disruptions due to problems with production and/or quality of raw materials and drugs).In 2020, the disruption of the global supply chain led to a sharp decline in the production of final branded drugs in the US.Using a monopoly on the production of raw materials, China dictated prices, and disruption of logistics dramatically increased transport costs and reflected in the prices of final pharmaceutical products in the US.In addition, a distinctive feature of global pharma is the circular nature of logistical dependence.US problems getting raw materials from China entailed to some extent delays in the supply of certain materials to China from the US.
The motivation of this study is that pharmaceutical technology has never been such an urgent need in the aging society and pandemic situation.Recent studies on COVID-19 economic effects confirm that during the pandemic, telecommunication and pharmaceutical industry are less affected or even been fostered [13].Considering the unique characteristics of both markets, studying how the US and China pharmaceutical sectors react in COVID crisis may provide policy makers to adjust policy quickly in future crisis and manage sector's volatility in advance.Specifically, this paper is focusing on the market situation, market volatility on pharmaceutical sectors during COVID-19 outbreak to evaluate how pharmaceutical industries of China and the United States changed.SSE Healthcare Industry Index (SSEHC) and S&P Health Care index (SPXHC) are selected as dependent variables, other independent variables including composite market index (S&P 500 index and SSE composite index), economic policy uncertainty (EPU) and volatility index (VIX) are applied to test the hypothesis.
This paper contributes to the knowledge relating the impact on financial markets during the COVID-19 pandemic.Currently, most of studies are concentrating on the effect of COVID-19 outbreak on overall stock market performance, while study on sectors with unusual performance is rare.Therefore, to analyze the pharmaceutical industry in two different markets during pandemic would provide more reference information to investors, helping them do rational trading behaviors, meanwhile, which would provide governments an industry-level sight to apply effective policies in future crisis.Lastly, pharmaceutical industry managers could take measures to reduce non-systematic risks.

Literature review
Prior studies have confirmed the negative impacts of public emergencies (terrorist attack, pandemics, earthquakes, etc.) on stock markets.The effect of emergency events is limited in geography, country, and time span, although they cause severe damage to stock markets.In general, these studies consider emergency events as points, and analyze before and after changes.
Chen (2007) has applied an event-study approach to Taiwanese hotel stock, proving that the SARS outbreak had a significant negative impact on hotel stocks in Taiwan and since the first case was found the SARS-related news reinforced the panic sentiment of investors [2][3][4][5][6].Gunay and Kurtulmus (2020) and Alfaro (2020) found that the unexpected change of infection cases could predict US stock market returns in real time during the COVID-19 pandemic [7].When an unexpected change occurred, the stock market would drop 4%-11%, and when infection cases dropped or did not match the expected change, the stock market would rebound.
In short, most studies have confirmed that public emergencies, including public health Previous studies related to effects of infectious diseases on stock market returns have used several quantitative measures to define impact factors and market volatility is used as a representative market volatility proxy in most studies.Ichev (2017) studied the impact on the stock market across several countries, concluding that the geography contributed to the volatility of the market, although intense media coverage is another factor that increased stock volatility [8].Onali's study (2020) shed light on COVID-19 effects on market volatility, using GARCH and Markov-Switching models, the study finds that the negative effects of market volatility on stock markets are intensified at the beginning of COVID-19 [8].A reasonable conjecture is that market volatility explains the abnormal performance of the pharmaceutical industry.Therefore, the second hypothesis is: H2: The COVID-19 outbreak change the relationship between pharmaceutical stock returns and market volatility.
Baker et al. ( 2016) created a news-based economic policy uncertainty index (EPU) to track policy impacts on firm-level stocks and other economic indicators, several empirical studies quote EPU as a factor to measure policy uncertainty on stock markets, which effectively reflects the time-varying changes on policy and market sentiments [9,10].Based on EPU studies have shed light on how policy adjustment affect markets at different pandemic stages.Sun et al. (2020) found that in the first few months of the pandemic, news reports related to COVID-19 situation provoked positive investor sentiment [11].Liu (2021), by tracking media-based indexes such as Google trend, Baidu index (most popular search engine in China) clarified a correlation between media-based index, stock market return, and market volatility [12].By analyzing the US stock market performance with (EPU) since 1900, Baker et al. (2020) argues that the US stock market volatility during the pandemic was provoked by the government's strict restriction against COVID-19 and has had a severe impact on economic activities than any previous pandemic [9,10].By introducing the EPU index, the study found that the unprecedented market volatility during COVID-19 was not directly caused by the pandemic but by policy changes.Bakers' study provides inspiration for studying policy effects at the micro-level during the crisis.Therefore, to evaluate economic policy changes may provide an explanation for the abnormal performance in pharmaceutical industries, and the therefore we hypothesize: H3: The COVID-19 outbreak changed the relationship between pharmaceutical stock returns and economic policy.
In short, previous studies revealed the relationship between public emergency events and stock market performance and pointed out that during the COVID-19 crisis, telecommunication and pharmaceutical industries performed differently.Several findings clarified that market volatility and policy changes may be the reason for the abnormal stock market performance.Findings of some of the research focused on macro-level changes during emergency events, for example, taking a country's financial market as study objects, which narrows the scope to a general level.The COVID-19 outbreak, as a systemic shock, leads to idiosyncratic results across sectors.Prior studies indicate a COVID-related impact across industries including the pharmaceutical industry but did not present a mechanism of influence.Analyzing the pharmaceutical industry may provide an industry-directed explanation.

Methodology
The dependent variables are the daily return of Shanghai stock Exchange Health Care Historical index and of S&P 500 Health Care index.VIX, CNVIX, VDAX-NEW (volatility proxy), composite stock market index (market proxy), and EPU, CNEPU (economic policy uncertainty proxy) are considered as independent variables in this study.
VIX is an index obtained from the weighted average implied volatility of index options (CBOE VIX White paper).By aggregating the weighted prices of puts and calls of S&P 500 index, means volatility is treated as the expectation of market risk.China CIVIX (CNVIX) is based on the CSI 300 index option contract listed in the China Financial Futures Exchange, which reflects investors' expectations of the volatility of China's A-share market in the next 30 days.VDAX-NEW is the implied volatility of the Frankfurt stock exchange and it has been widely accepted as a European stock market volatility index.The economic policy uncertainty index (EPU) is following the measure by Baker et al., 2016.EPU reflects economic policy changes by tracking keywords from the top 10 paper-based media in the US.China economic policy uncertainty index (CNEPU) is introduced, following Huang and Luk's (2019) study which pointed out that Baker's EPU is monitoring China monthly economic policy uncertainty, but the selected news media are mainly reflecting Hong Kong's economic policy changes from English-based news agencies [11].As Hong Kong's economic system is independent of mainland China, we consider to apply Huang and Luk's CNEPU index.CNEPU covers ten leading daily Chinese newspapers and covers wide economic policy changes from Chinese-language newspapers.
In order to test hypotheses H1, H2, and H3, time series data are divided into pre-COVID and COVID periods.The pre-COVID period is from 02 Jan 2018 to 10 Mar 2020, the day before WHO declared COVID-19 to be a global pandemic.COVID period is from 11 Mar 2020 to Sep 2022.
All data serials are calculated by Campbell's method (1998) [13]: Where  , is the rate of return of index i (SSEHC, SPXHC, VIX …) at time t.Pt is the close price of each index at time t.In general, financial time series data grow exponentially, and therefore have an exponential trend.By logarithmic transformation and firstdifferencing, stochastic trends and non-stationarity can be identified.The economic sense of  , is the growth rate of return on series.
According to the descriptive analysis (see Table 2), SSEHC and SSEC both have positive mean values in the pre-COVID period and a negative mean in the COVID period, suggesting a downward trend.The standard deviations of SPXHC have a slight increase.Most sample data, except China's EPU index in pre-COVID period, have a thick-tailed distribution (+3 kurtosis) and this character is commonly found among economic data, suggesting a Student's distribution should be applied in modeling the processes.This study applies a generalized auto-regressive conditional heteroskedasticity model (GARCH), based on the ARCH model (Engle, 1982), to analyze daily returns of pharmaceutical stocks in the Chinese and US market, by comparing the correlation between pharmaceutical proxies and independent variables in two periods testing hypotheses [14] are GARCH parameters, describing the impact of one lagged squared conditional variance, t= (1,2, 3…number of obs).

EGARCH model
Nelson (1991) suggested an exponential GARCH process to define the asymmetry effect.By defining the variance equation as follows: Where  is a constant;  is the ARCH parameter;  is the GARCH parameter.If  ≠ 0, the impact of the residual from the mean equation has no asymmetry effect.Lin (2018) confirmed that compared with GARCH, EGARCH performed more effectively and accurately on China stock market return rates [12].

Threshold GARCH model
Threshold GARCH has been developed on the basis of GARCH, Zakoian (1994) defined the variance equation of TGARCH as: Where  −1 2  −1 is an asymmetric term,  is the ARCH parameter;  is the GARCH parameter. −1 is a dummy variable, when  −1 < 0,  −1 =1;  −1 > 0,  −1 =0.If  ≠ 0, the return has no asymmetry effect.4. Model selection GARCH, TGARCH, and EGARCH are used in this study.Among them, TGARCH and EGARCH are used to examine leverage and asymmetric effects in time series data.According to Akaike information criterion (AIC), Schwarz Criterion (SC) and Hannan-Quinn criterion (HQ), the GARCH model is the best fitting in Chinese and the US Pre-COVID dataset.EGARCH is used in the US COVID period series and TGARCH is used in the China COVID series.The interpretation of the results is mainly based on the selected model.Additional ARCH-LM test (Table 4) presents a serial heteroscedasticity test.Pvalues of F-statistics have insignificant value in most series, except the US pre-COVID period, indicating heteroskedasticity is eliminated by ARCH process, and therefore, ARCH processes are effective.During the COVID window (see Table 8), the market index (SSEC) still has a strong impact on SSEHC to a significant level.Co-movement between SSEHC and market index (SSEC) is still positive.Therefore, H1 (the relationship between pharmaceutical sectors and stock market has changed) is rejected, as coefficients of the stock market are significant in both periods.Chinese market volatility (CNVIX) has a negative coefficient in a sub-significant level, and VADX-NEW index has become a new explanatory variable, although it contributes little with a coefficient of 0.028.H2 (the relationship between pharmaceutical sectors and market volatility has changed) has been accepted.EPU has an insignificant level in the COVID period, H3 (the relationship between pharmaceutical sectors and economic policy uncertainty has changed) has been accepted.The coefficient of ARCH and GARCH terms are both significant, and the sum of them is lower than 1.The coefficient (-0.146) of the asymmetric effect is significant, which means good news generates a bigger impact on pharmaceutical companies than bad news does.The coefficient of the ARCH term indicates that previous volatility could affect present shocks.To conclude, a comparison between the two periods shows that Chinese pharmaceutical companies are still highly correlated with the overall market.During COVID, CNVIX was less effective in terms of volatility in the pharmaceutical industry, and volatility from Europe contributes little to SSEHC performance, and CNEPU is no longer a significant variable during the COVID period.Table 9 provides pre-COVID results of the correlation between the US pharmaceutical sector and the dependent variables.It can be seen in the pre-COVID period, the S&P 500 health care is only positively correlated with the market index (S&P500).Market volatility and economic policy changes did not have any effects on the US pharmaceutical industry.ARCH term (0.15) and GARCH term (0.65) coefficients are both significant and sum to 0.80 which is close to 1, proven that the current shocks on the US pharmaceutical stock may have been caused by previous shocks, and such effect would persist in the long term.The asymmetric term is not significant in this period.

Discussion
The purpose of this article is to illustrate the response of the U.S. and Chinese pharmaceutical industries during COVID-19 by testing whether the COVID-19 outbreak has altered the relationship between pharmaceutical stocks and the independent variables, including market conditions, market volatility, and economic uncertainty.As previous studies have discussed the impact of the pandemic on economic activities, the employment rate, and stock markets overall, and pointed out the heterogeneity of the effect of COVID-19 on stock market volatility (Baker et al., 2020).This study illustrates the convergence between pharmaceutical industries and other industries, as (Sun (2021) and Chousa et al.
(2022)) found that pharmaceutical stock prices performed differently during the outbreak [9,11,15].The empirical results exhibit that before COVID-19, pharmaceutical sectors in China and the US are mainly affected by the overall fluctuation of the stock market.European volatility contributed to effects on the Chinese pharmaceutical industry, as discussed, the European and US pharmaceutical markets are the most important terminal for China's raw materials and the fluctuation in the EU market could affect the Chinese pharmaceutical industry.The finding is in line with other related studies.Sun (2021) and Baek (2020) pointed out that the US pharmaceutical industry was boosted after the outbreak, and among all sectors, pharmaceutical sectors have suffered minimal effects [11,15].The European volatility index affected the Chinese pharmaceutical industry during the pandemic.On the other hand, the US pharmaceutical industry has made a significant change in its relationship with VIX.The increased volatility of the market would pose a positive effect on the US pharmaceutical industry and the reason may divide into two points of view.First, the pharmaceutical industry became a golden investment track during the outbreak, as investors had strong expectations of the development process of wonder drugs or vaccines.When market volatility increased, investors tended to buy stocks in the pharmaceutical sector for excess returns.Second, the pharmaceutical industry may play the role of an asset haven during the crisis.Chai (2021) and Basher (2016) examined the correlation between gold price and volatility index, concluded that gold, a popular safe-haven asset in general, has a positive reaction with market volatility [6,7].Market volatility and the US pharmaceutical stocks during COVID period were consistent with market volatility and gold.Namely, during COVID period, pharmaceutical stocks may have been considered as a temporary safe-haven asset to avoid fluctuations from external effects.
The role of media-based index: economic policy uncertainty is to trace the impact from policy changes, it has only been found positively correlated with China pharmaceutical industry before the outbreak of the pandemic.In the rest of the period, it effects were insignificant, indicating COVID-19 related restrictions had minimal effects on the healthcare sector, although Baker et al. (2020) argue that policy changes were the driving force of a severe stock market volatility during pandemic outbreak [9,10].Or, to some extent, the policy shocks to the pharmaceutical industry have been offset by government aid or sharply rising market demand.
Asymmetric effects have been found in both countries during COVID.In the Chinese market, good news could have more impacts on the pharmaceutical industry.Investors are much more likely to invest in Chinese pharmaceutical stocks when in a bullish market.The reverse situation happened in the US pharmaceutical stocks, the bad news generating more impacts.

Conclusion, Contribution and Implication
The COVID-19 pandemic caused immeasurable economic damage while markets and governments have had to reconsider the development of the biopharmaceutical industry.An analysis of the pharmaceutical market performance could help governments and investors adjust their strategies in time for the next crisis.This study summarizes some key differences, tested by comparing the performance of pharmaceutical company stocks before and after the pandemic in China and the US.The empirical results suggest that pharmaceutical companies are mainly affected by overall market performance in all periods and US pharmaceutical companies performed differently in relation to market volatility during the COVID period.China pharmaceutical stocks are suffering the effects of EU market volatility.Although prior studies pointed out policy change could explain the abnormal performance in stock markets, in this study pharmaceutical industry stocks in both countries are not affected by policy changes during the COVID period.An asymmetric effect is found in both markets, but it functions differently.
There are several findings from this study.From a regulatory perspective, timely and accurate measures to reduce or to mitigate sector volatility when encountering public health crises should be taken.In this study, stocks in the US pharmaceutical industry during the pandemic were negatively correlated with market volatility, which requires policies to be able to identify the particularities of the sector and adopt a correct policy and macro-level policy changes would have an insignificant effect on the pharmaceutical industry.For investors, identifying volatility factors early in a crisis can help reduce losses from market volatility.Investors should remain sensitive to the pandemic development and pay attention to the impact of major economic and political changes in the sector.The results of this study will help both investors in forming an investment strategy and state administrations in building economic policy in relation to the pharmaceutical industry.
This study has some limitations.First, the sample size is not large enough to analyze COVID-19 pandemic over the whole period, and COVID-19 is still having impact on human lives.Second, it would be interesting if more external factors were considered in the study, as this study only examines the effects from three dimensions (Market composite, Market volatility, EPU).Third, further discussion on the difference between pharmaceutical industry performance in China and the US is not available, as COVID-19 has become a comprehensive crisis affecting economic activities in different ways.A simple examination of pharmaceutical company performances is not a convincing measure to explain the situation.In addition, future studies could go further into the question of what factors affect the US pharmaceutical industry regarding the negative relationship with market volatility.

Fig. 1 .
Fig. 1.China and the US Population ages 65 and above.(Source: The World Bank)

Table 1 .
Top pharmaceutical companies' stock prices 2019-2022 Q1 (Units in USD/share) ://doi.org/10.1051/e3sconf/202343107039emergencies, have negative impacts on stock markets across countries, and their duration varies by type of emergency.The hypothesis of this study is based on several concerns.First, prior studies found public emergencies have negative impacts on the overall stock market, but within COVID period, the telecommunication and pharmaceutical industries were not affected.To know how pharmaceutical sectors reacted to COVID situation, it is necessary to evaluate what has changed with COVID-19, and we hypothesize: H1: The COVID-19 outbreak changed the relationship between pharmaceutical industry stock returns and the stock market composite index. https

Table 2 .
Descriptive statistics for China Pre-COVID and COVID periods First difference of return on Shanghai stock Exchange Health Care Historical Index; SSEC: First difference of return on Shanghai stock Exchange Composite; CNVIX: First difference of return on Chinas' VIX; VIX: First difference of return on U. S VIX; VDAX: First difference of return on VDAX-NEWS; CNEPU: First difference of return on Chinas' Economic Policy Uncertainty indexTable3provides information of US proxies showing that the US S&P 500 index and S&P 500 health care index experienced a mild upward trend in the two periods.This difference may indicate a heterogeneity in behavior between the Chinese and US pharmaceutical markets.The same distributions of datasets are observed, except EPU indexes, other series do not have Gaussian distribution.

Table 3
Descriptive statistics for the Pre-COVID and COVID periods in US PRE-U.S: pre-COVID period; AFT-U.S: COVID period; SPXHC: First difference of return on S&P 500 Health Care index return; SP500: First difference of return on S&P 500 composite index return; VIX: First difference of return on U. S VIX; DAX: First difference of return on VDAX-NEWS; EPU: First difference of return on U. S Economic Policy Uncertainty index.

Table 4
ARCH-LM test

Table 5
provides two-period (Pre-COVID and COVID) correlations between variables in the Chinese pharmaceutical stock market.Before the COVID period, The Chinese pharmaceutical index was positively correlated with the market index and China EPU to a significant level and during the COVID period, SSEHC is only significantly correlated with the China Volatility index, suggesting that during the pandemic, investor's decisions on the China pharmaceutical industry changed.

Table 5
Correlation Probability Pre & COVID periods China -Table6illustrates the correlation between variables in the US market.It can be seen the US pharmaceutical industry has a tight correlation with the volatility index and VDAX-NEW index in two periods, and EPU has insignificant value in both periods.

Table 6
Correlation Probability Pre & COVID periods the US

Table 7
GARCH Estimation in Pre-COVID period China

Table 8
GARCH Estimation in COVID period China

Table 9
GARCH Estimation in pre-COVID period the US During the COVID period (seeTable 10), however, the growth rate of S&P500 healthcare (SPXCH) index has a positive correlation with market volatility index in a significant level, although the market index still has strong and significant correlation with SPXHC.H1 has therefore been rejected.The positive coefficient of VIX is indicating an increase in market volatility would increase the growth rate on US health care index, which is opposite to the result of Chinese pharmaceutical sector.The possible reason is the intensification of the pandemic has stimulated production and investment in US pharmaceutical industry.In this case, H2 has been accepted.Comparing with two periods, economic policy did not pose significant effect on US pharmaceutical industry, and the H3 is rejected.ARCH and GARCH coefficients are both significant in 1% level and the sum of both coefficient is close to 1, indicating past market shock on return rate can explain current volatility changes, and such relationship is long-lasting.Asymmetric effect in EGARCH process is significant at 1% level,  = 0.067 indicates the US pharmaceutical industry react differently to good/bad news during pandemic period.In short, unlike pre-COVID period, the US health ://doi.org/10.1051/e3sconf/202343107039care index has a significant positive correlation with VIX during pandemic, indicating when market volatility increase, pharmaceutical companies have better perform on stock return, and pharmaceutical companies are more sensitive on what is happening in the market in both periods. https

Table 10 GARCH
Estimation in COVID period the US