The Impact of US Economic Policy Uncertainty Shock on GCC Stock Market Performance

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Abdullah Alqahtani ◽  
Michael Taillard
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
The United States ◽  
Policy Uncertainty ◽  
Market Returns ◽  
Stock Market Returns ◽  
Gcc Countries ◽  
Stock Market Performance ◽  
Oil Markets ◽  
The Impact

Abstract This study examines the impact of the United States’ Economy Policy Uncertainty (US EPU) shocks on the Gulf Cooperation Council (GCC) countries’ stock market returns which are heavily related through global oil markets. Using monthly data spanning from 31/01/2010 to 31/08/2018, we employ a Non-Structural Vector Autoregression (VAR) and Vector Granger Causality Tests (VGCT) in order to ascertain the magnitude of transmitted shocks and to primarily evaluate if US EPU affects stock market returns in any of the GCC countries. Our OLS and VAR results suggest that US EPU has little impact on the GCC markets with the exception of Bahrain. The Vector Granger Causality Test confirms that changes in US EPU influence returns on Qatar’s stock market. These results will help GCC nations to stabilize global energy markets and prevent economic ripples to policy shocks.

scholarly journals US Economic Policy Uncertainty and GCC Stock Market Performance

2020 ◽  
Vol 15 (1) ◽  
pp. 223-242
Author(s):  
Saeed Abdullah
Keyword(s):  
Economic Policy ◽  
Saudi Arabia ◽  
Stock Market ◽  
Policy Uncertainty ◽  
Market Returns ◽  
Stock Market Returns ◽  
Economic Policy Uncertainty ◽  
Gcc Countries ◽  
Stock Market Performance ◽  
Economy Policy

AbstractThe study evaluates the effect of economy policy uncertainty of US on gulf cooperation council (GCC) countries’ stock market returns. The GCC countries are Saudi Arabia, Qatar, UAE, Kuwait, Bahrain and Oman. Granger Causality Tests (GCT) was done primarily to evaluate if economy policy uncertainty granger cause on GCC stock market returns. The analysis established that oil prices granger cause stock market returns for Saudi Arabia, Kuwait and UAE; the same is not true on changes in economic policy uncertainty of US cause on the stock market returns. Changes in economy policy uncertainty in US granger causes on stock market returns of Bahrain. On the other hand, economy policy uncertainty in US does not cause stock market returns in Qatar, UAE, Kuwait and Saudi Arabia. Vector Autoregression (VAR) analysis establishes that economy policy uncertainty in US negatively responds to the stock market returns of the GCC 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.

scholarly journals Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis

2020 ◽  
Vol 17 (18) ◽  
pp. 6729 ◽  
Author(s):  
Ștefan Cristian Gherghina ◽  
Daniel Ștefan Armeanu ◽  
Camelia Cătălina Joldeș
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Exchange ◽  
Causality Analysis ◽  
Market Returns ◽  
Stock Market Returns ◽  
Quantitative Evidence ◽  
Granger Causality Analysis ◽  
Gold Silver ◽  
The Impact

This paper examines the linkages in financial markets during coronavirus disease 2019 (COVID-19) pandemic outbreak. For this purpose, daily stock market returns were used over the period of December 31, 2019–April 20, 2020 for the following economies: USA, Spain, Italy, France, Germany, UK, China, and Romania. The study applied the autoregressive distributed lag (ARDL) model to explore whether the Romanian stock market is impacted by the crisis generated by novel coronavirus. Granger causality was employed to investigate the causalities among COVID-19 and stock market returns, as well as between pandemic measures and several commodities. The outcomes of the ARDL approach failed to find evidence towards the impact of Chinese COVID-19 records on the Romanian financial market, neither in the short-term, nor in the long-term. On the other hand, our quantitative approach reveals a negative effect of the new deaths’ cases from Italy on the 10-year Romanian bond yield both in the short-run and long-run. The econometric research provide evidence that Romanian 10-year government bond is more sensitive to the news related to COVID-19 than the index of the Bucharest Stock Exchange. Granger causality analysis reveals causal associations between selected stock market returns and Philadelphia Gold/Silver Index.

scholarly journals Nexus between Stock Market Returns and Economic Variables: Evidence

2017 ◽  
Vol 4 (01) ◽  
Author(s):  
Vanitha Chawla ◽  
Shweta .
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Indian Stock Market ◽  
The Impact

The paper examines the impact of selected macroeconomic variables on the Indian stock market. The macroeconomic variables used in the study are interest rate, exchange rate, index of industrial production (IIP) and gold price. BSE Sensex is used as proxy for Indian stock market. We have used the monthly data for all the variables from January 2001 to December 2016. Regression analysis and Granger Causality test is used to establish the relationship between the stock market and macroeconomic variables. The results show significant impact of only exchange rate on stock returns. All the other variables have shown insignificant impact on the stock market returns. The results of Granger causality test show unidirectional relationship between exchange rate and stock prices and bi-directional relation between IIP and SENSEX.

scholarly journals Euro-Mediterranean Financial Markets Reaction to Political Elections

2021 ◽  
Vol 6 (2) ◽  
pp. 70-85
Author(s):  
Jihene Ghouli Oueslati ◽  
Nadia Basty ◽  
Lamis Klouj
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Abnormal Returns ◽  
Anomalous Behavior ◽  
Market Returns ◽  
Stock Market Returns ◽  
Mediterranean Countries ◽  
Market Disruption ◽  
Stock Market Performance ◽  
The Impact

This paper studies a sample of Euro-Mediterranean countries to test the link of political-financial interdependencies. We focus specifically on the impact of the occurrence of national elections on the reaction of financial markets. We used the GARCH (1,1) model and the concept of the volatility multiplier to test our hypotheses. The results established that political elections have a significant impact on stock market performance and volatility for Euro-Mediterranean countries. We detected anomalous behavior in stock market returns. Stock market returns on election day and in the days following the election are inversely higher as uncertainty about the election outcome decreases. Investor uncertainty, combined with the consequences of the multiparty system in Euro-Mediterranean countries, leads to negative abnormal returns around elections. In terms of volatility, we found that the greater degree of uncertainty about the situation and the market disruption affected by the media and social networks increase volatility before election day.

scholarly journals The Impact Of Weekly Money Supply Announcements ON Stock Market Returns: A Multiprocess Mixture Model Approach

2011 ◽  
Vol 9 (3) ◽  
pp. 100
Author(s):  
James P. LeSage ◽  
Andrew Solocha
Keyword(s):  
Stock Market ◽  
Money Supply ◽  
Mixture Model ◽  
The United States ◽  
Multiple Models ◽  
Efficient Markets ◽  
Market Returns ◽  
Stock Market Returns ◽  
Efficient Markets Hypothesis ◽  
The Impact

This study provides evidence concerning the impact of anticipated and unanticipated components of the weekly money supply announcements on stock market returns in the United States and Canada on the date after the announcement. The innovative aspect of this study is the use of a multiprocess mixture model recently proposed by Gordon and Smith (1990) for modeling time series that are subject to several forms of potential discontinuous change and outliers. The technique involves running multiple models in parallel with recursive Bayesian updating procedures which extend the standard Kalman filter. The results provide strong evidence in favor of the efficient markets hypothesis that only the unanticipated component of the money supply announcement influences the stock market returns in both the United States and Canada.The use of OLS estimated in the present study produces results which suggest that both anticipated and unanticipated components of the money supply announcement exert a statistically significant influence on stock market returns in both countries. In contract, the multiprocess mixture model estimation method produces results which support the efficient markets hypothesis. The difference in findings between OLS and multiprocess estimation methods is attributed to the ability of the multiprocess techniques to model discontinuous structural shifts in the parameters and accommodate outliers in the stock return-weekly money relationship. The multiprocess mixture method provides evidence that numerous discontinuities and outliers exist in the stock market returns-weekly money relation and produces posterior probabilities for the multiple models running in parallel. These probabilities suggest that the OLS model has low posterior probability relative to the structural shift and outlier models which suggest poor inferences regarding the significance of anticipated and unanticipated money arise from the use of OLS estimation techniques.

Sign in / Sign up

Export Citation Format

Share Document