scholarly journals The The Impact of the Exchange Rate Volatility on Stock Markets Dynamics in Tunisia and Turkey: An Artificial Neural Network Analysis

2021 ◽  
pp. 1-21
Author(s):  
Nesrine Mechri ◽  
Christian De Peretti ◽  
Salah BEN HAMAD
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Exchange Rate ◽  
Stock Market ◽  
Multiple Regression ◽  
Stock Markets ◽  
Exchange Rate Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Impact

The present research provides an overview of links between exchange rate volatility and the dynamics of stock market returns in order to identify the influence of several macroeconomic variables on the volatility of stock markets, useful for political decision makers as well as investors to better control the portfolio risk level. More precisely, this research aims to identify the impact of exchange rate volatility on the fluctuations of stock market returns, considering two countries that belong to the Middle East and North Africa (MENA) zone: Tunisia and Turkey. Previous works in the literature used very specified and short periods of study, many important variables were neglected, and most of the earlier research was concentrated on the developed countries. In this research, we integrate several control variables of stock market returns that have not been simultaneously studied before. In addition, we spread out our research period up to 15 years including many events and dynamics. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and multiple regression models are first employed. Then, an Artificial Neural Network (ANN) is used and compared with the results of the multiple regression. Hence, the results show that for both Tunisia and Turkey, exchange rate volatility has a significant effect on stock market fluctuations.

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.

Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bijoy Rakshit ◽  
Yadawananda Neog
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Emerging Economies ◽  
Market Performance ◽  
Exchange Rate Volatility ◽  
Oil Price ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Stock Market Performance

Purpose The purpose of this paper is to investigate the effects of exchange rate volatility, oil price return and COVID-19 cases on the stock market returns and volatility for selected emerging market economies. Additionally, this study compares the market performance in the emerging economies during the COVID-19 pandemic with the pre-COVID and global financial crisis (GFC) period. Design/methodology/approach The authors apply the arbitrage pricing theory to model the risk-return relationship between the risk-based factors (exchange rate volatility and COVID-19 cases) and stock market returns. By applying the exponential generalized autoregressive conditional heteroskedasticity model, the study captures the asymmetric volatility spillover from the stock markets to foreign exchange markets and vice versa. Findings Findings reveal that exchange rate volatility exerts a negative and significant effect on the market returns in Brazil (BOVESPA), Chile (S&P CLX IPSA), India (SENSEX), Mexico (S&P BMV IPC) and Russia (MOEX) during the coronavirus pandemic. Regarding the effect of oil price returns, the authors find a positive relationship between oil price and stock market returns across all the economies in the study. The market returns of Russia, India, Brazil and Peru appeared more volatile during the pandemic than the GFC period. Practical implications As the exchange rate volatility is causing higher risk and uncertainty in the stock market’s performance, the central bank’s effort to maintain a stabilizing effect on the exchange rate sale can be proven crucial for the economies under consideration. Emphasized should also be given to boost investors’ confidence in the stock market, and for this, the government policy actions in reducing the transmission of the disease are the need of the hour. Originality/value While a large volume of literature on stock market performance in times of COVID-19 has emerged from developed economies, this study adds to the literature by exploring the emerging economies’ stock market performance during the COVID-19 pandemic. Unlike previous literature, this study examines the volatility spillover between stock and exchange rate markets in the worst affected emerging economies during the crisis.

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.

scholarly journals The Impact of Covid-19 Spread on Stock Markets: The Case of the GCC Countries

2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Market Index ◽  
Stock Market Return ◽  
Gcc Countries ◽  
Developed Stock Markets ◽  
The Impact

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.

Is the impact of the ECB Monetary Policy on EMU stock market returns asymmetric?

2009 ◽  
pp. 145-180
Author(s):  
Oreste Napolitano
Keyword(s):  
Monetary Policy ◽  
Stock Market ◽  
Stock Markets ◽  
Asymmetric Effect ◽  
Market Returns ◽  
Stock Market Returns ◽  
Fully Integrated ◽  
Markov Switching Models ◽  
Dynamic Relationship ◽  
The Impact

This paper explore, using Markov switching models, the dynamic relationship between stock market returns and the monetary policy innovation in 11 EUM countries and, for five of them, at each single industry portfolios. It also investigates the possibility of asymmetric effects of the ECB decision when stock markets are not fully integrated. The findings indicate that there is statistically significant relationship between policy innovations and stock markets returns. The findings from country size and industry portfolios indicate that monetary policy has larger asymmetric effect on the industry portfolios of big countries (Italy, France and Germany) compared to the same sectors of small countries (Netherlands and Belgium).

scholarly journals Impact of Macroeconomic Variables on Karachi Stock Market Returns

2018 ◽  
Vol 10 (2) ◽  
pp. 28 ◽  
Author(s):  
Javed Pervaiz ◽  
Junaid Masih ◽  
Teng Jian-Zhou
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Secondary Data ◽  
Research Process ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Index Value ◽  
The Impact

The study investigated The study examines the impact of selected macroeconomic variables (inflation, exchange rate, interest rate) on Karachi stock market returns. Mainly secondary data used in the research process. The study consists of data for the period of 10 years and 5 months starting from January 2007 till May 2017. For this purpose, monthly data of KSE-100 index has been observed for the period January 2007 to May 2017. The market returns have been calculated through the opening and closing index value of each month. The inflation, interest rate, and exchange rate has been taken as independent variables. Hypotheses have been tested to find out whether there exists a significant relationship between the Stock market return and macroeconomic variables or not. To test this hypothesis, Regression analysis used and results are calculated through Stata software.

scholarly journals Impact of Terrorism on Stock Market: A Case of South Asian Stock Markets

2019 ◽  
Vol 5 (2) ◽  
pp. 215-242
Author(s):  
Rehana Kousar ◽  
Zahid Imran ◽  
Qaisar Maqbool Khan ◽  
Haris Khurram
Keyword(s):  
Sri Lanka ◽  
Stock Market ◽  
South Asia ◽  
Stock Markets ◽  
Stock Exchange ◽  
Spillover Effect ◽  
Market Returns ◽  
Stock Market Returns ◽  
Negative Effect ◽  
The Impact

The purpose of this study is to examine the impact of terrorism on stock markets of South Asia namely, Karachi Stock Exchange 100 index (Pakistan), Bombay Stock Exchange (India), Colombo Stock Exchange (Sri Lanka) and Chittagong Stock Exchange (Bangladesh). Monthly panel data has been used for the period of January 2000 to December 2016. Terrorism events happened during the period of 2000 to 2016 have been incorporated to examine the impact of terrorism on stock market returns of South Asia. DCC GARCH through R software is used to analyze the impact of terrorism on stock market returns and to analyze the spillover effect of terrorism in one country and on the stock markets of other countries of South Asia. The results indicate that terrorism has significant and negative effect on stock market returns of Pakistan, India and Bangladesh but insignificant in Sri Lanka. Results also shows that stock markets return of Pakistan, India, and Bangladesh are significant and positively correlated with each other except the Stock market of Sri Lanka.

scholarly journals Analysis of ARIMA-Artificial Neural Network Hybrid Model in Forecasting of Stock Market Returns

2020 ◽  
pp. 42-53
Author(s):  
Yakubu Musa ◽  
Stephen Joshua
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Stock Market ◽  
Hybrid Model ◽  
Market Returns ◽  
Stock Market Returns ◽  
Artificial Neural ◽  
Modelling And Forecasting

This study focuses on the modelling of Nigerian stock market all–shares index and evaluations of predictions ability using ARIMA, Artificial Neural Network and a hybrid ARIMA-Artificial Neural Network model. The ARIMA (1,1,1) model and neural network with architecture (6:1:3) turns out to be the most fitted among the considered models, these models were used for forecasting the returns, and their performances have been compared according to some statistical measure of accuracy. A hybrid model has been constructed using ARIMA-Artificial Neural Networks model, the computational results on the data reveal that the hybrid model using Artificial Neural Network, provides better forecasts, and will enhance forecasting over the single ARIMA and Artificial Neural Networks models. The study recommends the use of ARIMA-Artificial neural network for modelling and forecasting stock market returns.

scholarly journals NATURAL DISASTERS — BLESSINGS IN DISGUISE?

2016 ◽  
Vol 61 (01) ◽  
pp. 1640004 ◽  
Author(s):  
HARDJO KOERNIADI ◽  
CHANDRASEKHAR KRISHNAMURTI ◽  
ALIREZA TOURANI-RAD
Keyword(s):  
Stock Market ◽  
Natural Disasters ◽  
Stock Markets ◽  
Volcanic Eruptions ◽  
Negative Effects ◽  
Market Returns ◽  
Stock Market Returns ◽  
Limited Impact ◽  
The Impact

This study examines the impact of natural disasters on stock market returns and on industries that are likely to be affected by such disasters. We find that different natural disasters have different effects on stock markets and industries. Our evidence suggests that while earthquakes, hurricanes and tornadoes could negatively affect market returns several weeks after the events, other disasters such as floods, tsunamis and volcanic eruptions have limited impact on stock markets. We also find that construction and materials industry is generally positively affected by natural disasters but non-life and travel industries are likely to suffer negative effects.

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