Impact of Macroeconomic Variables on Stock Market Returns: A Case of Karachi Stock Exchange

Author(s):  
Ihsan Ilahi ◽  
Mehboob Ali ◽  
Raja Ahmed Jamil
2017 ◽  
Vol 9 (2) ◽  
pp. 206
Author(s):  
Saseela Balagobei

The stock market is one of the most energetic sectors that play an important role in contributing to the wealth of the economy. It plays a crucial role in the economic growth and development of an economy which would benefit industries, trade and commerce as a whole. The aim of this study is to investigate the impact of macroeconomic variables on stock market returns in Sri Lanka. Dependent variable of this study is stock market return measured by All Share Price Index (ASPI) and All Share Total Return Index (ASTRI) and independent variables are macroeconomic variables, such as Interest Rate (IR), Inflation Rate (INF), Exchange Rate (ER), Factory Industry Production Index (FIPI) and money supply (MS).  The study targets all the companies listed and active in Colombo Stock Exchange (CSE) from 2006 to 2015. For analysis, secondary data was collected from annual reports of Central bank of Sri Lanka, Colombo Stock Exchange, Securities and Exchange Commission and Department of Census and Statistics. The results of the study reveal that the stock market returns is influenced by macroeconomic variables except money supply in Sri Lanka. Interest rate and factory industry production have negative influence on stock market return in Colombo Stock exchange while inflation rate and exchange rate have positive influence on stock market return. The findings of the study may be useful to public and economy especially stock market investors to focus the macroeconomic variables for making their effective decisions in order to enhance their stock market returns.


2017 ◽  
Vol 64 (2) ◽  
pp. 233-243 ◽  
Author(s):  
Md. Abu Hasan ◽  
Anita Zaman

Abstract This paper examines the volatility of the Bangladesh stock market returns in response to the volatility of the macroeconomic variables employing monthly data of general index of Dhaka Stock Exchange (DSE) and four macroeconomic variables (Call Money Rate, Crude Oil Price, Exchange Rate and SENSEX of Bombay Stock Exchange) from January 2001 to December 2015. The results of GARCHS models reveal that the volatility of DSE return is significantly guided by the volatility of macroeconomic variables, such as, exchange rate and SENSEX. Specifically, volatility of the DSE is expected to 19% increase by 1% increase of exchange rate. Moreover, the volatility of the Bangladesh stock market returns is expected to dampen down by 2% with an increase in the volatility of Indian stock market of 1%. Thus, we can comment that adding exchange rate or stock returns of India in the GARCH model provides significant knowledge about the behaviour of the DSE volatility.


2021 ◽  
Vol 18 (4) ◽  
pp. 280-296
Author(s):  
Abdel Razzaq Al Rababa’a ◽  
Zaid Saidat ◽  
Raed Hendawi

Different models have been used in the finance literature to predict the stock market returns. However, it remains an open question whether non-linear models can outperform linear models while providing accurate predictions for future returns. This study examines the prediction of the non-linear artificial neural network (ANN) models against the baseline linear regression models. This study aims specifically to compare the prediction performance of regression models with different specifications and static and dynamic ANN models. Thus, the analysis was conducted on a growing market, namely the Amman Stock Exchange. The results show that the trading volume and interest rates on loans tend to explain the monthly returns the most, compared to other predictors in the regressions. Moreover, incorporating more variables is not found to help in explaining the fluctuations in the stock market returns. More importantly, using the root mean square error (RMSE), as well as the mean absolute error statistical measures, the static ANN becomes the most preferred model for forecasting. The associated forecasting errors from these metrics become equal to 0.0021 and 0.0005, respectively. Lastly, the analysis conducted with the dynamic ANN model produced the highest RMSE value of 0.0067 since November 2018 following the amendment to the Jordanian income tax law. The same observation is also seen since the emerging of the COVID-19 outbreak (RMSE = 0.0042).


Author(s):  
Robert D. Gay, Jr.

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies. However, what is the relationship between share prices and economic activity in emerging economies? The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model. Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research. Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.


Author(s):  
Adekunle Orelope Koleosho ◽  
Folajimi Festus Adegbie ◽  
Ayooluwa Olotu Ajayi- Owoeye

Sustainability of shareholder’s wealth has been a subject of discussion globally due to various decisions of the managers and the effect it has on company’s performance. Various corporate actions and information about the companies are disseminated over time and studies have shown the effect on shareholder's wealth. This study examined the effect of capital market returns on sustainability of shareholder's wealth in Nigeria Listed Companies. The study adopted ex-post facto research design. A sample of 57 companies from a target population of 168 companies listed on the Nigerian Stock Exchange (NSE) as December 2018 was randomly drawn across the various market sectors for the panel data. The study used secondary data from the NSE, CBN and companies’ data on the Bloomberg Terminals. Validity and reliability were premised on the statutory audit of the financial statement. The study adopted descriptive and inferential (Regression and Correlation) statistics to analyze the data. The study found that the stock market returns indicators (dividend per share, earnings and Leverage) have joint and statistically significant relationship with market price per share: DPS, EPS and LEV with Adjusted R2 = 0.738, F(3, 796) = 54.74, p = 0.108 > 0.05. The study concluded that stock market returns measured by dividend and earnings have a significant effect on the shareholders' wealth while leverage exerts a negative effect on Market Price per share. The study recommended that the management of the companies should embrace the payment of dividend to shareholders while ensuring the growth of earnings over the period to sustain shareholder's wealth.


2017 ◽  
Vol 13 (1-2) ◽  
pp. 52-69
Author(s):  
Gagan Deep Sharma ◽  
Mrinalini Srivastava ◽  
Mansi Jain

This article examines the relationship between six macroeconomic variables and stock market returns of 13 emerging markets from Latin America, Europe, Africa and Asia in the context of global financial crisis of 2008. The findings reveal some commonality in determination and variation of returns with macroeconomic variables from pre-crisis (1st January 2005–31st March 2009) to post-crisis period (1st April 2009–31st March 2016). Further, results show co-integration among most of the macroeconomic variables depicting significant implications for investors and policymakers.


Author(s):  
Emeka Nkoro ◽  
Aham Kelvin Uko

This chapter investigates the relationship between volatility of macroeconomic variables and the volatility of Nigeria’s stock market returns using annual data from 1985-2009. The Macroeconomic variables used are: inflation rate, government expenditure, foreign exchange rate, index of manufacturing output, broad money supply, and minimum rediscount rate. In pursuance of this, the AR(1)-GARCH-X(1,1) model was used for the analysis. The findings of this study revealed that, Nigeria’s current stock market return is positively influenced by previous returns. Volatility of Nigeria’s stock market returns was affected by past volatility less than the related news from the previous period. Also, the result shows that there is a significantly positive relationship between the volatility of the Nigeria’s stock market returns and the short run deviations of the macroeconomic variables (macroeconomic factors volatility) in the system. The results provide some insight to investors, financial regulators, and policymakers in the Nigeria’s stock market when structuring their portfolios and formulating economic and financial policies.


Sign in / Sign up

Export Citation Format

Share Document