Stock Market Vulnerability to the COVID-19 Pandemic: Evidence from Emerging Asian Stock Market

2020 ◽  
Vol 11 (2) ◽  
pp. 126
Author(s):  
Ayoub RABHI
Keyword(s):  
Panel Data ◽  
Stock Market ◽  
Exchange Rates ◽  
Stock Markets ◽  
Oil Price ◽  
Daily Growth ◽  
Behavioral Component ◽  
The Us ◽  
The Impact

This paper studies empirically the emerging Asian stock market vulnerability to pandemics. Taking the Covid-19 virus as a case study, we used the ARDL panel data approach to investigate the impact of the daily Covid-19 confirmed cases along with a behavioral component based on a triggering fear event related to news about Covid-19 deaths. The results indicate that both the reported daily growth of Covid-19 confirmed cases along with the triggering fear event related to news about death, affected the Asian stock markets performance negatively, other variables such as oil price, gold price, exchange rates, and the US stock market were also found to be determinants of the Asian stock markets during the studied period.

scholarly journals Opportunity or Crisis? Volatility and Leverage Effect in the World’s Largest Economies

2019 ◽  
Vol 9 (4) ◽  
pp. 1
Author(s):  
Amalendu Bhunia ◽  
Devrim Yaman
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Volatility ◽  
Future Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Us ◽  
The World ◽  
The Impact ◽  
The Relationship

This paper examines the relationship between asset volatility and leverage for the three largest economies (based on purchasing power parity) in the world; US, China, and India. Collectively, these economies represent Int$56,269 billion of economic power, making it important to understand the relationship among these economies that provide valuable investment opportunities for investors. We focus on a volatile period in economic history starting in 1997 when the Asian financial crisis began. Using autoregressive models, we find that Chinese stock markets have the highest volatility among the three stock markets while the US stock market has the highest average returns. The Chinese market is less efficient than the US and Indian stock markets since the impact of new information takes longer to be reflected in stock prices. Our results show that the unconditional correlation among these stock markets is significant and positive although the correlation values are low in magnitude. We also find that past market volatility is a good indicator of future market volatility in our sample. The results show that positive stock market returns result in lower volatility compared to negative stock market returns. These results demonstrate that the largest economies of the world are highly integrated and investors should consider volatility and leverage besides returns when investing in these countries.

Trade and tech uncertainty will boost ‘safer’ assets

2019 ◽  
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Price ◽  
Crude Oil Price ◽  
Government Bonds ◽  
Content Type ◽  
The Us ◽  
New Phase

Significance US President Donald Trump’s decision last month to intensify the US-China conflict by raising the tariff rate and targeting Chinese tech firms is straining stock markets and making government bonds more attractive. Marking a dangerous new phase, sentiment towards the tech sector is deteriorating, after powering the stock market 'bull run' for a decade. Impacts Uncertainty over both US policy and geopolitics globally will continue to make the dollar more attractive, outweighing Fed dovishness. Emerging markets enjoyed a surge in inflows from January-April 2019, but suffered sharp outflows in May, and investors will remain cautious. The VIX Index, Wall Street’s so-called ‘fear gauge’, has surged by around 50% since May 3, and is likely to remain elevated. Rising US output means that the Brent crude oil price is likely to stabilise rather than rebound, having fallen by about 20% since April.

The Impact of Monetary and Fiscal Policies on the Stock Market in the United States (U.S); Evidence from Linear ARDL Framework

2020 ◽  
Vol 11 (1) ◽  
pp. 132-132
Author(s):  
Aref Emamian
Keyword(s):  
United States ◽  
Stock Market ◽  
The United States ◽  
Real Effective Exchange Rate ◽  
Annual Data ◽  
Fiscal Policies ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
The Impact

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States

scholarly journals Volatility Modeling: An Overview of Equity Markets in the Euro Area during COVID-19 Pandemic

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1212
Author(s):  
Pierdomenico Duttilo ◽  
Stefano Antonio Gattone ◽  
Tonio Di Di Battista
Keyword(s):  
Stock Market ◽  
Euro Area ◽  
Risk Premium ◽  
Stock Markets ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Volatility Modeling ◽  
The Impact ◽  
Second Wave ◽  
Daily Returns

Volatility is the most widespread measure of risk. Volatility modeling allows investors to capture potential losses and investment opportunities. This work aims to examine the impact of the two waves of COVID-19 infections on the return and volatility of the stock market indices of the euro area countries. The study also focuses on other important aspects such as time-varying risk premium and leverage effect. This investigation employed the Threshold GARCH(1,1)-in-Mean model with exogenous dummy variables. Daily returns of the euro area stock markets indices from 4th January 2016 to 31st December 2020 has been used for the analysis. The results reveal that euro area stock markets respond differently to the COVID-19 pandemic. Specifically, the first wave of COVID-19 infections had a notable impact on stock market volatility of euro area countries with middle-large financial centres while the second wave had a significant impact only on stock market volatility of Belgium.

RESPONSE OF STOCK MARKET DURING COVID-19 AND 2008 FINANCIAL CRISIS: A COMPARATIVE EVIDENCE FROM BRICS NATIONS

2021 ◽  
pp. 1-24
Author(s):  
SANJEEV KUMAR ◽  
JASPREET KAUR ◽  
MOSAB I. TABASH ◽  
DANG K. TRAN ◽  
RAJ S DHANKAR
Keyword(s):  
South Africa ◽  
Financial Crisis ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
2008 Financial Crisis ◽  
First Case ◽  
Egarch Model ◽  
The 2008 Financial Crisis ◽  
The Impact

This study attempts to examine the response of stock markets amid the COVID-19 pandemic on prominent stock markets of the BRICS nation and compare it with the 2008 financial crisis by employing the GARCH and EGARCH model. First, average and variance of stock returns are tested for differences before and after the pandemic, t-test and F-test were applied. Further, OLS regression was applied to study the impact of COVID-19 on the standard deviation of returns using daily data of total cases, total deaths, and returns of the indices from the date on which the first case was reported till June 2020. Second, GARCH and EGARCH models are employed to compare the impact of COVID-19 and the 2008 financial crisis on the stock market volatility by using the data of respective stock indices for the period 2005–2020. The results suggest that the increasing number of COVID-19 cases and reported death cases hurt stock markets of the five countries except for South Africa in the latter case. The findings of the GARCH and EGARCH model indicate that for India and Russia, the financial crisis of 2008 has caused more stock volatility whereas stock markets of China, Brazil, and South Africa have been more volatile during the COVID-19 pandemic. The study has practical implications for investors, portfolio managers, institutional investors, regulatory institutions, and policymakers as it provides an understanding of stock market behavior in response to a major global crisis and helps them in taking decisions considering the risk of these events.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

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