scholarly journals An Investigation into Dynamic Conditional Correlation of Pakistan Stock Market with its Trade Partners – Under Covid-19 Perspective

2021 ◽  
Vol 10 (1) ◽  
pp. 100-118
Author(s):  
HINA SHAHRUKH ◽  
IMRAN ABBAS JADOON ◽  
RAHEEL MUMTAZ
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Positive Sign ◽  
Financial Contagion ◽  
Health Crisis ◽  
Dynamic Correlation ◽  
Market Participants ◽  
Market Dynamic ◽  
The Impact ◽  
Trade Partners

This study investigates the financial linkage of Pakistan stock market with those of its three major trade partners i.e., China, UK and USA and the impact of ongoing global health crisis (Covid-19) on this linkage. A Dynamic Conditional Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) approach was used to calculate dynamic correlation coefficient between the countries’ stock markets by using the daily price data of MSCI indices spanning the period 1st January 2016 to 31 December 2019 (Pre COVID-19 period) and 1st January 2020 to 30th June 2020 (COVID-19 period). The empirical results of the study highlighted that the integration of Pakistan stock market with the sampled countries was relatively low before the COVID 19 pandemic – which indicated a positive sign for market participants to diversify their portfolios. However, after the pandemic breakout, the correlation among stock markets increased substantially, indicating the significant role played by the shock events in the transmission of financial contagion between different stock markets. Keywords: Stock Market, Dynamic Conditions, Covid-19, Pakistan.

scholarly journals Financial contagion: The impact of the volatility of global stock exchanges on the Lima-Peru Stock Exchange

2020 ◽  
Vol 1 (1) ◽  
pp. 13-27
Author(s):  
Pedro Pablo Chambi Condori
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Exchange ◽  
Market Volatility ◽  
Financial Contagion ◽  
Stock Market Volatility ◽  
Important Indicator ◽  
Dynamic Correlation ◽  
High Volatility ◽  
The Impact

What happens in the international financial markets in terms of volatility, have an impact on the results of the local stock market financial markets, as a result of the spread and transmission of larger stock market volatility to smaller markets such as the Peruvian, assertion that goes in accordance with the results obtained in the study in reference. The statistical evaluation of econometric models, suggest that the model obtained can be used for forecasting volatility expected in the very short term, very important estimates for agents involved, because these models can contribute to properly align the attitude to be adopted in certain circumstances of high volatility, for example in the input, output, refuge or permanence in the markets and also in the selection of best steps and in the structuring of the portfolio of investment with equity and additionally you can view through the correlation on which markets is can or not act and consequently the best results of profitability in the equity markets. This work comprises four well-defined sections; a brief history of the financial volatility of the last 15 years, a tight summary of the background and a dense summary of the methodology used in the process of the study, exposure of the results obtained and the declaration of the main conclusions which led us mention research, which allows writing, evidence of transmission and spread of the larger stock markets toward the Peruvian stock market volatility, as in the case of the American market to the market Peruvian stock market with the coefficient of dynamic correlation of 0.32, followed by the Spanish market and the market of China. Additionally, the coefficient of interrelation found by means of the model dcc mgarch is a very important indicator in the structure of portfolios of investment with instruments that they quote on the financial global markets.

Through the Lens of Recession 2.0: Diversification Dynamics Between the Leading Asian Stock Markets

2021 ◽  
pp. 097226292098395
Author(s):  
Manu K. S. ◽  
Surekha Nayak ◽  
Rameesha Kalra
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Integration ◽  
Developing Economies ◽  
Positive Impact ◽  
Global Market ◽  
Stock Market Integration ◽  
Developed Economies ◽  
Market Participants ◽  
Causality Tests

The focus of this article is to analyse the inter-linkages between eight leading stock markets in Asian continent from the period of July 2011 to February 2018. This period holds relevance as this was the time when Recession 2.0 set in, which adversely affected the developed economies; however, the developing economies withstood the crisis without much of an impact. Co-integration and Granger causality tests were conducted to probe the inter-linkages. Study revealed a positive impact on Asian stock market indices collectively on each of the indexes. The highest number of unidirectional causalities was to KOPSI and NIFTY from rest of the stock indices. Results confirmed that no co-integration relationship existed among the selected indices indicating favourable diversification opportunities. Thus, the study fosters global market participants and policymakers to consider the nitty-gritties of stock market integration so as to benefit from international stock market diversification in the Asian region.

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.

scholarly journals Light a lamp and look at the stock market

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Radeef Chundakkadan
Keyword(s):  
Stock Market ◽  
Financial Distress ◽  
Investor Sentiment ◽  
Downside Risk ◽  
Bond Yields ◽  
Risky Assets ◽  
Market Participants ◽  
Market Return ◽  
The Impact

AbstractIn this study, we investigate the impact of the light-a-lamp event that occurred in India during the COVID-19 lockdown. This event happened across the country, and millions of people participated in it. We link this event to the stock market through investor sentiment and misattribution bias. We find a 9% hike in the market return on the post-event day. The effect is heterogeneous in terms of beta, downside risk, volatility, and financial distress. We also find an increase (decrease) in long-term bond yields (price), which together suggests that market participants demanded risky assets in the post-event day.

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.

scholarly journals Financial contagion and 2016 oil crisis: a factor analysis

2020 ◽  
Author(s):  
Turki Maya
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Principal Component ◽  
Financial Contagion ◽  
Market Returns ◽  
Component Structure ◽  
Stock Market Returns ◽  
Oil Crisis ◽  
Market Indexes ◽  
Variance Explained

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>

scholarly journals Rebalancing of exchange traded funds in stock market using option trading strategies

2021 ◽  
Vol 20 (3) ◽  
pp. 513-527
Author(s):  
Vinaykumar Elegeti
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Tracking Error ◽  
Threshold Value ◽  
Trading Strategies ◽  
Exchange Traded Funds ◽  
Dynamic Features ◽  
Financial Industry ◽  
Option Trading ◽  
The Impact

Motivation: The finance and academic industries are highly discussed in the stock market trading domain. The increase in economic globalization shows the connection among stock markets in different countries, which produces the effect of risk conduction in the market. Forecasting the direction of every day’s stock market return is important and challenging. The growing complexity and dynamic features in stock markets are difficult in the financial industry. The inflexible trading method developed by financial practitioners utilized a larger amount of stock market features and is failed to achieve a satisfactory result in every condition of the market. Further, the existing data mining approaches are incomplete and inefficient. Aim: To overcome the issues in stock and problem of existing methods, proposed option trading strategies for rebalancing Exchange Traded Fund (ETF) in the stock market. Rebalancing-ETF measure the volatility of the stock to track the error of model and rebalance the threshold quality to improve the trade. The proposed method increases the order of threshold quantity to rebalance the trade. Results: The result showed that the minimum orders increases in rebalancing trade, which reduces the impact of price formations in market. The tracking error occurs when the larger quantity of threshold value reduces the quantity. Then, the markets are changed significantly when the Net Asset Values (NAV) of rebalancing ETF increases.

Testing Market Reaction On Stock Market Delisting In Russia

2021 ◽  
Vol 15 (3) ◽  
pp. 14-27
Author(s):  
Елена Моисеевна Рогова ◽  
Maria Belousova
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Statistical Significance ◽  
Abnormal Returns ◽  
Global Market ◽  
Public Companies ◽  
Market Participants ◽  
Study Methodology ◽  
Available Information ◽  
The Impact

This paper expands the available information on the effects of delisting in Russia, and represents a rare empirical analysis of the impact of external events on securities prices in this major global market. We seek to evaluate how stock prices of competing companies fluctuate around the dates of stock market delisting announcements and completion. We analyse stock prices as correlated with company delisting events from 2004 to 2019 on 552 companies on the Russian MOEX Exchange. The event study methodology is used to evaluate the abnormal returns of rival companies close to relevant delisting dates. These data were checked for statistical significance using the standardised Patell residual test. The results indicate a significant competitive effect on stock prices both on the dates of delisting announcement and on completion, with more significant returns close to announcement dates. These effects were found to influence the prospects not just of individual groups of companies, but of all market participants. We may conclude from our results that delisting is not an event limited in effect to only one company, but impacts the industry as a whole, temporarily changing its value. As such, it will interest both shareholders and managers of public companies, and any participants of industries in which delisting occurs.

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