Examining causal relationship among stock market index, crude oil price, exchange rate amid COVID-19 era: an empirical evidence from Indian financial market using VAR model

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Abstract


The year 2020, so far, has been relentlessly wreaking havoc on the very concept of life and work as we know them. This unprecedented event has been unfolding multiple worst-case scenarios on all fronts of our society and has eclipsed almost every other natural disasters of the modern world and pushing humanity on the verge of tipping point. Up to now, more than 29 million people have been infected and more than 1000 thousand have lost their lives because of COVID-19. So far, this epidemic has not only taken human lives but also snatched the livelihood of millions of people worldwide. Because of this epidemic, the world has been experiencing a kind of regressive mindset, where countries are looking inward, and all kinds of political, social, and economic relations are in a very confused state on account of this ongoing assault on them. Consequently, this epidemic has triggered a high level of skepticism in investors about the certainty of the rapid healing of the social and economic condition which is hindering the quick and healthy recovery of financial markets in most of the pandemic ridden countries of the world. The purpose of this study was to examine the causal relationship among various factors such as crude oils price, exchange rate, and stock market performance during Covid-19 in the context of financial market performance in India. Several methodologies have been applied during this study such Johansen co-integration test, vector autoregression model, and Granger causality test. The results have supported a significant causality among crude oil prices and the exchange rate on stock market performance.


Full Text

Introduction COVID-19 has become a cliché for everyone across the globe. Since the initial outbreak of this pandemic in Wuhan, China in late December 2019 and early January 2020, this pandemic has incarcerated all kind of social, economic activities in the major parts of the world and the destructive impact of COVID-19 on the global economy and financial markets can be duly reflected in various reports, historical data, and research papers. The downward spiral in the global financial market began from the last week of February 2020 when almost every stock market reported massive losses, unbeknownst to the world since the 2008 financial crisis. That global meltdown corrected itself slightly in the first week of March, but the signal to investors already out and stock indices, highly volatile with large swings, brought in ultimate mayhem on the floors forcing investors to takeout their funds and resulting 9th March became “Black Monday” for the global financial market. Soon after “Black Monday” most European and North American financial markets faced another sharp fall which was more than 9%. During March 2020, the global financial market witnessed more than 25% of the slump (Reinicke, 2019). Though April 2020 was less volatile, the global financial market still was under the impression of the COVID-19 crisis and lower crude oil prices. During May 2020, US stocks and crude oil prices rebounded from deeply negative territory. After rallying by about 25% during April and May, June was rather modest for the S&P 500 as the benchmark index rose by about 1.8% only. Having said it, it still managed to post its third straight monthly gain. Although Dow Jones Industrial Average also followed suit, it would be the reflection of the ground reality. Initial gains were wiped out by a spike in COVID-19 case numbers in many parts of the United States as the month progressed. July witnessed a strong recovery pattern and lower volatility across major indexes. Despite the unabetted coronavirus case numbers, the S&P 500 is now in the green for 2020, riding on generally strong earnings from the largest U.S. companies and hopes for an imminent vaccine, most likely by end of 2020. The pattern observed so far in the Indian stock market are duly reflected by two major Indian market indices, Nifty and SENSEX, which recorded their worst performance on 23 March 2020 with fall of -12.98 and -13.15% respectively, only to be followed by a consistently upward trend with minor corrections. Literature review The literature review section aims to assess the impact of crude oil price, exchange rate dynamics in the currency market, and overall stock market performance in the backdrop of COVID-19, on the financial market performance in India. The Corona Virus already has tremendous effects on the macroeconomic state of the world with greater impacts to come. Nearly 31 million global cases of COVID-19 have now been recorded. World Health Organization's DirectorGeneral Dr. Tedros Adhanom stressed that behind these statistics, there is a great deal of pain and suffering (Ghebreyesu, 2020). As of mid-September, more than 950,000 thousand people have lost their lives due to COVID-19 as per Johns Hopkins University & Medicine. In addition to its human cost, the COVID-19 pandemic is impacting economies, employment, education, and health systems. As a result, the world is facing great recession and long-term recovery, which would need coordinated interventions from Governments and provision for effective treatments (Gopinath, 2020). With per capita income contracting in the largest fraction of countries globally since 1870, the rate of shrinkage for advanced economies is projected around 7% in 2020. That weakness will further drag the prospects for emerging market and developing economies, with a projected contraction of 2.5%. World Bank is forecasting global economy to shrink by 5.2% in year 20202. With the unprecedented uncertainty, the strength of the recovery is unpredictable and d economies are being pushed into massive lockdowns, with hope to contain the virus and save lives, but also threatening the worst recession since the Great Depression (Gopinath, 2020). The financial services industry in India stares at a crucially small window of opportunity to steer their economic outlook as the country contends with the ongoing coronavirus pandemic. Weaker consumption and a dwindling access to capital will contribute to an overall contraction in real GDP in next couple of years. The implications will be echoed across the industry, from lower borrowing for corporate and consumer to limited capacity for investment and weaker spending. However, Beyond the next couple of years, India's financial sector offers enormous growth potential should sources of risk, such as limited financial inclusion rates and barriers to foreign investment, be addressed. We begin by providing information about COVID-19 and its impact across the globe and in the context of India. The major impact areas across industries are investment returns and capital valuation around the world. The ongoing economic slowdown triggered by the outbreak will also lead to revenue crunch and a material increase in credit risk and a potential spike in insurance claims covering various commodities and events. The severity of this pandemic and its contagion effects has crippled value chains for organizations around the world. The supply and demand shock to the global economy is creating feedback loop of fall in consumer spending and a decrease in production potential across multiple industries. At the Macroeconomic level, although the impact of various stimulative monetary or fiscal policy measures taken by various governments has been some- what positive on credit markets, they are not able to mitigate the demand and supply shocks in the economy. The impact of COVID-19 on financial markets worldwide as a result of huge upheaval is evident in most of the recent studies, pretty much in every market. Nuhu A. Sansa (Sansa, 2020) found a significant effect of COVID-19 cases on the performance of the financial markets of China and America. D. Zhang (Zhang et al., 2020) also found a strong significance of COVID-19 on the global financial markets. During the study period, authors found that a higher number of COVID-19 cases were directly proportional to the higher level of risk in the global financial market. Similarly, A.M. Al-Awadhi (Al-Awadhi et al., 2020) reported in their study that COVID-19 effects negatively on the stock market return. A higher number of confirmed cases and a higher number of the death toll due to COVID-19, deteriorate stock market returns significantly. M.A. Estrada (Ruiz Estrada, 2020) indicates that the volatility of oil prices has historically been heavily impacted by pandemics such as COVID-19. D. Aloui (Aloui et al., 2020) employ the structural VAR model with timevarying coefficients and stochastic volatility to the impact of COVID-19 shocks on the energy futures markets, particularly on crude oil and natural gas S&P GS Indexes. The findings confirm that energy commodities S&P GS Indexes respond to COVID-19 shock that varying over time due to fundamentals factors as well as behavioural and psychological factors. The rapidly developing COVID-19 outbreak poses health risks to employees as well as financial risks and reporting uncertainty to all companies and their stakeholders. All of this translates into significant challenges for society as a whole. The UN’s International Labour Organization predicts 1.6 billion informal economy workers could suffer “massive damage” to their livelihoods. The UK, US, Canada, and various European and Asian countries have registered a huge loss in jobs which increases their rate of unemployment. International Monetary Fund Managing Director said “The human costs of the Coronavirus pandemic are already immeasurable and all countries need to work together to protect people and limit the economic damage” (Georgieva, 2020). Impact of COVID19 on India The economic disruption of the pandemic is proving extensive, leading to a downward revision to real GDP forecasts in 2020. A contraction of 4.5% for FY2020/21, followed by a rebound of 6% in FY2021/22 is on cards for India (Seth, 2020). The pandemic has serious implications for the financial industry. Data from the Centre of Monitoring Indian Economy show that India’s unemployment rate shot up to 23.4% in April and 23.5% in May 2020 (Kapoor, 2020). It recovered to 11.0% in June, but this is still higher than pre-crisis levels. Credit demand is waning due to an uncertain business outlook and lenders are also tightening lending standards in anticipation of an increase in loan delinquencies from September 2020. In the same way, according to R. Pembleton (Pembleton, 2020) forex market disruptions due to COVID-19 are having a profound impact on financial markets and will continue to do so for a long period. In the U.S., the unemployment rate has been mounting to levels higher than those reported during the peak of the great financial crisis and this has caused demand for the dollar to soar as investors seek a safe-haven currency. Hence US dollar appreciates against Indian rupees as well as other currencies. Similarly, in another latest study done by I. Banerjee (Banerjee et al., 2020) shows that under the combined lockdown period, from March 25 to April 27, a positive correlation between the increasing number of COVID-19 and the higher price of US dollar against Indian rupees which means Indian rupees is being depreciated with rising numbers of a confirmed case. This study focuses on the effect of macroeconomic variables such as crude oil price and currency exchange rate on the stock performance and this study also tries to see the effect of these macroeconomic variables on each other. Moreover, during the present course of the investigation, it would be interesting to examine the effect of stock market performance on these macroeconomic variables as well. Crude oil Like almost all industries, oil & gas is suffering from reduced demand and operational constraints during the COVID-19 outbreak. The nature of oil and gas and the structure of the market create peculiar issues. The industry has experienced and will experience a particularly sharp downturn. All aspects such as demand, prices, credit and equity markets, capital spen- ding, dividends, share buybacks as well as the geopolitical equations are impac- ted. In particular, political will and government appliances are playing a major role in shaping up the outcome of this crisis. During the initial phase of the crisis, Saudi Arabia and Russia failed to reach an agreement on output cuts to balance the market. Previously agreed-to production restraint had been abandoned and the market was flooded with oil. That significantly contributed to the oil price crash but post-agreement between those, the oil has rebounded but it is still around almost half of its price since the COVID-19 outbreak went global. The refining margins have collapsed as well as refinery utilization has dropped. One report of the U.S bureau of labor statistics, indicates that despite of some apparent benefits to some nations due to falling oil prices, the impact of lower oil prices on oil producing nations is nothing short of disastrous. Major oil importer countries managed to insulate themselves from this upheaval and they enjoyed low oil prices and strong financial market, whereas major exporter countries suffer a loss when oil prices dipped. Having said that, the cyclical nature of globalization is catching up very fast and as a result, a global slowdown is becoming more of a reality than ever before as demand-supply uncertainty is too complex to form a robust response strategy. In the light of above, working capital management has become the highest priority. Oil majors like Shell, Total and BP are cutting their capital expenditures and suspending or postponing share buyback programs. Reducing costs, rescheduling debt, consolidation will be the focus in the near-term and winners will be those with most improved balance sheets, lower breakeven prices. Financial necessity might force the strategic consolidation go hand in hand with financial restructuring. Assuming significant lag between capital investment cuts and production tapering, agreement amongst OPEC members on production could change things quickly and dramatically. Apart for current studies, there are several studies have been done to understand the relationship between financial market performance and crude oil prices. J. Park and R.A. Ratti in their study established direct connect between oil price shocks and stock markets but the magnitude of swing to positive or negative us depends on several factors. Once of the key deciding criterion, they established was whether the economy was an oil-importer or oil-exporter (Park, Ratti, 2008). R.-G. Cong revealed that different market conditions of an economy are the main trigger of a positive or negative relationship (Cong et al., 2008). Prof. HuiMing Zhu investigated the relationship between crude oil shocks and stock markets for the OECD and non-OECD panel from January 1995 to December 2009. He found that crude oil prices and stock prices have a feedback loop mechanism in place that supports each other in the long-run. They concluded that the asymmetric dynamic adjustment behaviour is indeed evident for these countries and it is dependent on country-specific mechanisms by which crude oil prices and disaggregated energy prices affect economic growth and stock prices (Zhu et al., 2010). Two independent studies, one by K. Jain (Jain, 2013) and the other by P. Strithar (Srithar et al., 2015) studied the impact that oil price volatility had on the economic indicators of India. They considered Gross Domestic Product (GDP), National Stock Exchange of India (NSE), and Inflation from 2003 to 2013 as variables to run simple regression to analyze the impact that crude oil prices had on them in India. They also corroborated the presence of a positive relationship between crude oil and the Stock market (NSE). Exchange rate There are several current studies during the time of the COVID-19 pandemic era as well as previous studies have been done to examine the effect of the exchange rate on the performance of the stock market. On account of lacking consensus on the underlying causality in the relationship between stock prices and exchange rates, several studies can be referenced suggesting contrasting notions. On one hand, portfolio balance models of exchange rate determination hypothesize a negative relationship between stock pri- ces and exchange rates, on the other hand, a positive causal relationship between stock prices and exchange is observed where a weakened currency makes local firms more competitive thus leads to an increase in their exports and in turn their stock prices. A study done by R. Aggarwal examined the influence of exchange rate changes on U.S. stock prices for the period from 1974 to 1978. They found a positive correlation between exchange rates and stock prices. His study showed that depreciation in the U.S. dollar causes declination in U.S. stock prices and vice versa (Aggarwal, 1981). Similarly, another study by M.H. Ibrahim examined dynamic interactions among GDP output, price level, money supply, exchange rate, and equity prices for the Malaysian Stock Market by applying cointegration techniques and vector autoregression on time series data. It found a positive effect of exchange rate on stock prices, which supported the findings that local currency appreciation moves the stock prices up and vice versa (Ibrahim, Yusoff, 2001). However, some earlier studies have found a negative relationship between exchange rate and stock prices in long run, but a positive relationship in the short run. For instance, S. Jawaid investigates the effects of fluctuations in exchange rate and interest rates on stock prices of banking sector in Pakistan. Cointegration results point to a significant causality in exchange rate and short-term interest rate movements and stock prices. On the other hand, a significant positive causality was noted in the exchange rate and interest rate volatilities and stock prices in the short run. Causality analysis confirms bidirectional causality between exchange rate and stock prices (Jawaid, Ul Haq, 2012). R. Ajayi showed that an upward aggregated domestic stock price pushes domestic currency valuation in short run but in the long-run, stock market growth has a positive effect on domestic currency value. However, currency depreciation has shown a negative knock-on impact on the stock market (Ajayi, Mougoue, 1996). Another study by K. Kim to examine the relation of industrial production, inflation, exchange rate, and interest rate with the S&P 500 Index reveals a negative relationship between inflation, exchange rate, and interest rate with the S&P 500 Index. However, a positive relationship between industrial production and the S&P 500 index stands out as an outlier (Kim, 2003). Based on the above, it can be assumed that there is a weak or no association between stock prices and exchange rates. The events influencing the exchange rates may be different from the drivers behind stock price movements. Some previous research works have corroborated that there is a very weak or no association between stock prices and exchange rates. B. Solnik examined the impact of several macroeconomic variables including exchange rates, on stock prices. He used monthly data from the U.S., Canada, and seven western European markets. He found that depreciation in native currency showed a positive yet insignificant effect on the U.S. stock market (Solnik, 1987). L. Rittenberg employed the Granger causality tests to examine the relationship between exchange rate changes and price level changes in Turkey. Since causality tests are sensitive to lag selection, therefore he employed three different specific methods for optimal lag. In all cases, he found that causality relationship from stock price volatility to exchange rate varies but there is no causal relationship from the exchange rate to stock price volatility (Rittenberg, 1993). Similarly, N. Muhhamad and A. Rasheed examined the impact of exchange rates of Asian countries on their stock market by deploying Vector Autoregression Model to analyze the causal relationship between variables and they found, no longrun or short-run causal relationship between the exchange rate and the Stork market of India and Pakistan (Muhammad et al., 2002). Similar observations were made for Bangladesh and Sri Lanka stock market, however, a bi-directional long-run causality between these variables was identified. The results suggested that in South Asian markets, there is little relation between stock prices and exchange rates, at least in the short run. Investors should not use information obtained from one market to predict the behaviour of the other market. In another study, H. Zhao by using Vector Autoregression and multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models found that there was not a stable long-term equilibrium relationship between RMB real effective exchange rate and stock price (Zhao, 2009). S. Suriani also found in their study that there was no relationship existed between exchange rate and stock price, and both the variables are independent of each other (Suriani et al., 2015). Methodological concept As the world is witnessing, the increasing number of COVID-19 cases and its global infestation has been causing an unprecedented adverse effect on every sector of the social and economic environment of the world. This disease is forced to reduce all kinds of activities in the manufacturing sector, transportation sector, service sector, public sector, etc. to its lower level. Hence, a high level of unemployment, a low level of crude oil demand, fluctuations in the exchange rate have been registered in this period. It is interesting to examine how much these variables have been affected during the COVID-19 pandemic crisis and how these variables affect each other during this economic environment. In this study statistical software Eviews10 has been employed to perform statistical analysis. In this study, we have analysed the causal relationship among the National Stock Exchange of India (NSE 50) stock market index, crude oil price, and exchange rate USD/INR. The empirical model In this study Vector Autoregression Model (VAR) has been deployed to examine the causal relationship among the chosen variables. Vector autoregression is a technique that is used by macroeconomists to examine the joint dynamic behaviour of a collection of variables without requiring strong restrictions of the kind needed to identify underlying structural parameters. It has become a prevalent method of time-series modelling. Originally Vector Autoregression Model was proposed by Sims in 1980 to address the dynamic relationship among variables and subsequently, VAR models became popular among academicians and researchers as a tool, to handle largescale models in applied macroeconomics. An empirical model of A VAR system contains a set of n variables, each of which is expressed as a linear function of p lags of itself and all of the other n - 1 variable, plus an error term. A simple VAR model with two variables a and b, an order-p VAR would be the two equations:

About the authors

Maneesh Kumar Pandey

St. Petersburg National Research University of Information Technologies, Mechanics, and Optics

Author for correspondence.
Email: maneeshban@gmail.com
9 Lomonosova St, Saint Petersburg, 191002, Russian Federation

master student, Department of Economics and Management

Irina G. Sergeeva

St. Petersburg National Research University of Information Technologies, Mechanics, and Optics

Email: igsergeeva@gmail.com
9 Lomonosova St, Saint Petersburg, 191002, Russian Federation

Doctor of Economics, Professor, Faculty of Technological Management and Innovations

Vishal Gudla

HSE University

Email: vishalgudla@gmail.com
3A Kantemirovskaya St, Saint Petersburg, 194100, Russian Federation

master student, Department of Management, St. Petersburg School of Economics and Management

References

  1. Abu Bakar, N., & Rosbi, S. (2020). Impact of coronavirus disease 2019 (COVID-19) to equity market and currency exchange rate. IOSR Journal of Economics and Finance, 11(2), 22-31.
  2. Aggarwal, R. (1981). Exchange rates and stock prices: A study of the U.S. capital markets under floating exchange rates. Akron Business and Economic Review, 12, 7-12.
  3. Ajayi, R.A., & Mougouė, M. (1996). On the dynamic relation between stock prices and exchange rates. Journal of Financial Research, 19(2), 193-207.
  4. Al-Awadhi, A.M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
  5. Aloui, D., Goutte, S., Guesmi, K., & Hchaichi, R. (2020). COVID-19’s impact on crude oil and natural gas S&P GS Indexes. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3587740
  6. Banerjee, I., Kumar, A., & Bhattacharyya, R. (2020). Examining the effect of COVID-19 on foreign exchange rate and stock market - an applied insight into the variable effects of lockdown on indian economy. arXiv preprint:2006.14499
  7. Cong, R.G., Wei, Y.M., Jiao, J.L., & Fan, Y. (2008). Relationships between oil price shocks and stock market: An empirical analysis from China. Energy Policy, 36(9), 3544-3553.
  8. Dickey, D.A., Jansen, D.W., & Thornton, D.L. (1994). A primer on cointegration with an application to money and income. Cointegration (pp. 9-45). Palgrave Macmillan, London.
  9. Dickey, D.A., & Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427. https://doi.org/10.2307/2286348
  10. Georgieva, K. (2020). The great lockdown: Worst economic downturn since the great depression. Press release no. 20/98. International Monetary Fund.
  11. Ghebreyesu, A.T. (2020). WHO Director-General’s opening remarks at the media briefing on COVID-19 - 18 March 2020. Retrieved January 19, 2021, from https://www.who.int/ director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-mediabriefing-on-covid-19---18-march-2020
  12. Gopinath, G. (2020). New predictions suggest a deeper recession and a slower recovery. World Economic Forum Agenda 2020. Retrieved December 5, 2020, from https://www.weforum.org/agenda/2020/06/imf-lockdown-recession-covid19-coronaviruseconomics-recession/
  13. Ibrahim, M.H., & Yusoff, S.W. (2001). Macroeconomic variables, exchange rate and stock price: A Malaysian perspective. International Journal of Economics, Management and Accounting, 9(2). Retrieved June 17, 2021, from https://journals.iium.edu.my/ enmjournal/index.php/enmj/article/view/70
  14. Jain, K. (2013). Oil price volatility and its impact on the selected economic indicators in India. International Journal of Management and Social Sciences Research, 2(11)
  15. Jansen, J. (1991). Fitting regression models to ordinal data. Biometrical Journal, 33(7), 807-815. https://doi.org/10.1002/bimj.4710330707
  16. Jawaid, S.T., & Ul Haq, A. (2012). Effects of interest rate, exchange rate and their volatilities on stock prices: Evidence from banking industry of Pakistan. Theoretical & Applied Economics, 19(8)
  17. Kapoor, M. (2020). India's unemployment rate shoots to 23.5% in April: CMIE. Business Today. Retrieved November 12, 2020, from https://www.businesstoday.in/current/economypolitics/india-unemployment-rate-april-cmie-highest/story/402589.html
  18. Kim, K.H. (2003). Dollar exchange rate and stock price: Evidence from multivariate cointegration and error correction model. Review of Financial Economics, 12(3), 301-313.
  19. Muhammad, N., Rasheed, A., & Husain, F. (2002). Stock prices and exchange rates: Are they related? Evidence from South Asian countries (with comments). The Pakistan Development Review, 41(4), 535-550.
  20. Murphy, A., Plante, M., & Yücel, M. (2015). Plunging oil prices: A boost for the US economy, a jolt for Texas. Economic Letter, 10(3), 1-4.
  21. Park, J., & Ratti, R.A. (2008). Oil price shocks and stock markets in the US and 13 European countries. Energy Economics, 30(5), 2587-2608.
  22. Pembleton, R. (2020). What’s the impact on forex trading? Refinitiv. Retrieved November 12, 2020, from https://www.refinitiv.com/perspectives/market-insights/covid-19-whats-theimpact-on-forex-trading/
  23. Reinicke, C. (2019). Goldman Sachs now says US GDP will shrink 24% next quarter amid the coronavirus pandemic - which would be 2.5 times bigger than any decline in history. Business Insider. Retrieved April 1, 2020, from https://markets.businessinsider.com/news/stocks/us-gdpdrop-record-2q-amid-coronavirus-recession-goldman-sachs-2020-3-1029018308
  24. Rittenberg, L. (1993). Exchange rate policy and price level changes: Casualty tests for Turkey in the post-liberalisation period. The Journal of Development Studies, 29(2), 245-259.
  25. Ruiz Estrada, M.A. (2020). The impact of COVID-19 on the world oil prices. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3583429
  26. Sansa, N.A. (2020). The impact of the COVID-19 on the financial markets: Evidence from China and USA. Electronic Research Journal of Social Sciences and Humanities, 2(II), 29-39.
  27. Seth, D. (2020). COVID-19 impact: IMF projects Indian economy to contract by 4.5% in FY21. Special on Coronavirus. Business Standard. Retrieved November 12, 2020, from https://www.business-standard.com/article/economy-policy/imf-cuts-india-growth-forecastto-4-5-for-fy21-6-4-percentage-point-cut-120062401488_1.html
  28. Solnik, B. (1987). Using financial prices to test exchange rate models: A note. The journal of Finance, 42(1), 141-149.
  29. Srithar, P., Bairavi, N., & Mariselvam, G. (2015). Oil price volatility and its impact on the selected economic indicators in India. International Academic Research Journal of Economics and Finance, 3(4), 10-16.
  30. Suriani, S., Kumar, M.D., Jamil, F., & Muneer, S. (2015). Impact of exchange rate on stock market. International Journal of Economics and Financial Issues, 5(1S).
  31. World Health Organization. (2020, August 10). COVID-19. Retrieved December 5, 2020, from https://www.who.int/director-general/speeches/detail/who-director-general-s-openingremarks-at-the-media-briefing-on-covid-19---10-august-2020
  32. Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 101528. https://doi.org/10.1016/j.frl.2020.101528
  33. Zhao, H. (2010). Dynamic relationship between exchange rate and stock price: Evidence from China. Research in International Business and Finance, 24(2), 103-112
  34. Zhu, H.-M., Li, S.-F., & Yu, K. (2011). Crude oil shocks and stock markets: A panel threshold cointegration approach. Energy Economics, 33(5), 987-994. https://doi.org/10.1016/ j.eneco.2011.07.002

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