scholarly journals Reconciling Macroeconomic Determinants with Stock Market Performance in Selected Sub-Saharan African Countries: an ARDL Approach

2020 ◽  
Vol 1/2020 (13) ◽  
pp. 23-39
Author(s):  
Kareem Abidemi Arikewuyo ◽  
◽  
Akeem Adekunle Adeyemi ◽  
Eunice Titilayo Omodara ◽  
Lateef Adewale Yunusa ◽  
...  
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Price ◽  
Market Performance ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Macroeconomic Factors ◽  
Stock Market Performance ◽  
Sub Saharan ◽  
Macroeconomic Determinants

Prior studies have adduced unstable macroeconomic factors to stock price movement overtime but the relationship between the duo remained unsettled. Autoregressive Distributed Lag (ARDL) technique was used to reconcile the macroeconomic determinants with performance of stock markets in selected Sub-Saharan Africa (SSA) covering the period of 1999:1–2017:4. It was found that macroeconomic indicators were essential in determining stock market performance in Nigeria while South African stock market did not show any predictable linkage but the contemporaneous effect of oil price changes on stock market performance in selected SSA. The study, therefore, recommended that countries in SSA should reduce overdependence on oil to minimize external influence in order to promote stability of the stock markets.

scholarly journals The Regime-Switching Behaviour of Exchange Rates and Frontier Stock Market Prices in Sub-Saharan Africa

2021 ◽  
Vol 14 (3) ◽  
pp. 122
Author(s):  
Maud Korley ◽  
Evangelos Giouvris
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Regime Switching ◽  
Markov Switching ◽  
Sub Saharan Africa ◽  
Var Model ◽  
High Volatility ◽  
Sub Saharan ◽  
The Relationship ◽  
Fx Market

Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.

The Effects of Macroeconomic Factors on the Performance of Stock Market in Sri Lanka

2018 ◽  
Vol 3 (6) ◽  
pp. 33-41 ◽  
Author(s):  
Shohani Upeksha Badullahewage
Keyword(s):  
Sri Lanka ◽  
Stock Market ◽  
Exchange Rates ◽  
Interest Rates ◽  
Stock Exchange ◽  
Market Performance ◽  
Vital Role ◽  
Sri Lankan ◽  
Macroeconomic Factors ◽  
Stock Market Performance

The main objective of this research is to analyze the vital impact of macroeconomic factors on the stock market performance in Sri Lanka. All the factors which have a direct impact on the working of the emerging stock market have hereby studied. The relationship between the pivotal factors such as inflation, gross domestic product, interest rates, and exchange rates has been properly conducted with the assistance of the indexes. The results of the analysis revealed that all these factors have an inseparable impact over the performance of the stock market and Sri Lankan stock market performance has eventually over gone through many ups and downs because of them as well. It has been revealed that among all the factors that have been discussed, inflation and exchange rates have comparatively higher effects on the stock market performance. It shows a fluctuation because of the unpredictable nature of these factors. Colombo Stock Exchange has seen a tremendous change in its performance over a period for which these factors have played a prominent as well as a vital role in it its functioning.

scholarly journals Deconstructing the Impact of Entrepreneurship on Income Inequality in Sub-Saharan Africa Countries

2020 ◽  
Vol 34 (1) ◽  
pp. 273-284
Author(s):  
Jimoh S. Ogede
Keyword(s):  
Income Inequality ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Macroeconomic Factors ◽  
Significance Level ◽  
Long Run ◽  
Short Run ◽  
Sub Saharan ◽  
Entrepreneurial Activities ◽  
The Impact

Abstract The study examines the impacts of entrepreneurship on income inequality in a panel of 29 Sub-Saharan African countries spanning from 2004 to 2020. The paper employs a dynamic heterogeneous panel approach to differentiate between long-run and short-run impacts of entrepreneurship on income inequality. The findings establish a robust and direct nexus between entrepreneurial activities and income disparity. The results of the two entrepreneurial indicators are stable. Besides, the coefficient of the human capital is positive in the regression and statistically significant at a 5 percent significance level. The proxies for macroeconomic factors exhibit diverse signs and impact, which suggest a policy stimulus aimed at refining macroeconomic situations and also ignite prospects for households to increase their incomes.

scholarly journals Impact of Covid-19 on Stock Market in Sub-Saharan Africa

2021 ◽  
Vol 1 (2) ◽  
pp. 41-70
Author(s):  
Saifullahi Adam Bayero ◽  
Babangida Danladi Safiyanu ◽  
Zaitun Sanusi Bakabe
Keyword(s):  
Stock Markets ◽  
Negative Impact ◽  
Virus Disease ◽  
Selection Criterion ◽  
Sub Saharan Africa ◽  
World Health ◽  
African Countries ◽  
The World ◽  
Sub Saharan ◽  
The Impact

Corona virus disease (COVID-19) which was declared by the World Health Organization as a global pandemic caused serious economic problem to all the countries including Sub-Saharan Africa. Given the negative impact of COVID19 on the world economy, this paper examined the impact of COVID19 related cases and death on stock exchange markets volatility in Sub-Saharan African countries. The study used the number of reported cases and death from four Sub-Saharan African countries viz Nigeria, South Africa, Kenya, and Botswana, reported cases and death from China and U.S. and all share index as a proxy of stock markets in four countries from 28 February 2020 to 21 December 2020. The study estimated GARCH 11, TGARCH 11, and EGARCH 11 since the variables are heteroskadestic in nature which makes the application of ARCH lausible; the selection criterion was based on Akaike, Schwarz, and Hannan info Criteria. The result shows that COVID19 confirmed cases and death do not affect the operation of the stock markets in Sub-Saharan African countries, but the volatility of the markets has increased within the period of analysis. Furthermore, Botswana and Kenya stock markets were affected by external cases from China. We therefore recommended that stock markets stakeholders in Sub-Saharan Africa should be more concern about health safety measures and be ready for any future pandemic that might affect the markets.

scholarly journals Relative Stock Market Performance during the Coronavirus Pandemic: Virus vs. Policy Effects in 80 Countries

2021 ◽  
Vol 14 (4) ◽  
pp. 177
Author(s):  
Richard C. K. Burdekin ◽  
Samuel Harrison
Keyword(s):  
Latin America ◽  
Stock Market ◽  
Stock Markets ◽  
Market Performance ◽  
Government Support ◽  
Geographical Region ◽  
Full Sample ◽  
Policy Effects ◽  
Market Effects ◽  
Stock Market Performance

This paper examines relative stock market performance following the onset of the coronavirus pandemic for a sample of 80 stock markets. Weekly data on coronavirus cases and deaths are employed alongside Oxford indices on each nation’s stringency and government support intensity. The results are broken down both by month and by geographical region. The full sample results show that increased coronavirus cases exert the expected overall effect of worsening relative stock market performance, but with little consistent impact of rising deaths. There is some evidence of significantly negative stock market effects arising from lockdowns as reflected in the Oxford stringency index. There are also positive reactions to government support in March and December in the overall sample—combined with some additional pervasive effects seen in mid-2020 in Latin America.

Extreme learning machine for stock price prediction

2021 ◽  
pp. 002072092098467
Author(s):  
Fangzhao Zhang
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Extreme Learning Machine ◽  
Stock Price ◽  
Market Performance ◽  
Market Analysis ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Stock Market Performance ◽  
Learning Machine

Stock market performance prediction has always been a hit research topic and is attractive due to its strong potential to generate financial profit. Being able to predict future stock price in a relatively accurate way forms a significant task of stock market analysis. Different mechanisms from fundamental analysis to statistical modeling have been deployed to study stock market performance and various factors from fundamental factors, technical factors to market sentiments are also incorporated in the stock price prediction task. However, due to the chaotic stock market performance, which is close to random walk, and the difficulty in discerning influential factors, predicting stock price faces a lot of challenges. In recent years, fast development in fields such as machine learning has offered new ways to look at this task. In this paper, we employ Extreme Learning Machine (ELM) algorithm, a recent modification of traditional feedforward neural network with single hidden layer, whose learning speed is greatly improved based on solid mathematical background and capability to circumvent problems such as local minimum is also enhanced, to construct an ELM combination model to study stock market performance and predict stock price. A comparison between the predicted output and the real data is carried out to test the feasibility of applying ELM model to stock market analysis. The result indicates that ELM model is desirable for predicting stock price variation trend while some inaccuracy exists in the prediction of peak values, which may require further model modification. Overall, by applying the machine learning model ELM to predict stock price and generating desirable outcome, this paper both contributes to offering a new way to investigate stock market performance and enlarging the field deployment of ELM model as well.

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