scholarly journals The Effect of Macroeconomic Variables on Stock Prices in Emerging Sri Lankan Stock Market

2010 ◽  
Vol 6 (1) ◽  
pp. 50 ◽  
Author(s):  
LMCS Menike
2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.


2010 ◽  
Author(s):  
Bekir Elmas ◽  
Ömer Esen

The stock price has a close relationship with some macroeconomic variables. As examples of the main macroeconomic variables can be shown that exchange rates, inflation, interest rate, growth rates. This paper empirically examined the relationship between the local stock market indexes and exchange rate (USD) in six Eurasian countries namely Turkey, Germany, France, Netherlands, Russia, France and India. The paper set out by testing existence of a long-term relationship between considered two variables using the Engle-Granger (1987), Johansen (1988, 1995) and Johansen-Juselius (1990) cointegration methods. Results of Engle- Granger cointegration test showed that there is no cointegration linkage between two variables under consideration. Furthermore, The Johansen cointegration test found that there is a long-term relationship between two variables (variables in the two countries). Under the VAR (Vector Autoregressive) and VEC (Vector Error Correction) models appllied the Granger causality test, revealed an unidirectional casual relationship between two variables in each of the six countries. In addition as regards the relationship While there is a unidirectional causal relationship running from exchange rate to stock market for four countries. However this relation is casual running from stock market to exchange rate for other two countries. According to the direction of the relationship these results that relationship between stock prices and exchange rate in four countries supports for the “Traditional Approach”. Furthermore, this relation also supports for the “Portfolio Approach” for other two countries.


Pravaha ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 64-82
Author(s):  
Dipendra Education Karki

This study empirically examines the macro-economic factors of the stock market performance in Nepal. It considers the annual data of four macroeconomic variables; real GDP, inflation, interest rate and broad money supply from 1994 to 2016 and attempts to reveal the relative influence of these variables on stock prices represented by ‘NEPSE Index’ of the Nepalese capital market. Empirical results reveal that the performance of stock market is found to respond positively to real GDP, inflation and money supply, and negatively to interest rate. More importantly, cointegrating evidence cannot be found between macroeconomic variables and stock market index which suggests that stock price movements in Nepal are not explained by the macroeconomic variables. It supports random walk hypothesis in Nepalese stock market.Pravaha Vol. 24, No. 1, 2018, Page: 64-82


Author(s):  
Neeru Gupta ◽  
Ashish Kumar

This study investigates the long-term and short-term relationships between selected macroeconomic variables and the selected Indian stock market sector indices over the period of 2010 to 2017. The Johansen Co-integration Test, the Vector error correction model (VECM), is applied to calculate the long-term and short-term relationship between sector indices and macroeconomic variables. It is found that stock prices are exposed to macroeconomic factors, but the level of sensitivity is different in different sectors. Out of five sectors taken in the study, it is found that only the realty sector has long run relationship with macroeconomic variables. Other sectors have no long run relationship with macroeconomic variables. Along with this, it is also found that the Auto index has a significant short-term positive relationship with gold prices and the FMCG sector index has a significant short-term positive relationship with industrial production. The consumer price index and exchange rate have significant short run relationship with realty sector index.


2021 ◽  
pp. 097215092199049
Author(s):  
Preeti Sharma ◽  
Avinash K. Shrivastava

The current study intends to find out the linkages between crude oil prices and economic activity in the context of Indian economy. The macroeconomic variables such as gross domestic product (GDP), unemployment, industrial output, inflation, exchange rate and stock market prices have been used as a proxy to economic activity. We have analysed the sample data of 30 years, that is, from year 1991 to 2020. To inspect the short-run relationship between oil prices and the above-mentioned macroeconomic variables, Granger causality test has been applied after removing the presence of unit root through differencing the series. To investigate the long-run relationship, vector error correction model (VECM) has been applied after testing cointegration through the Johansen method of cointegration. The findings of the study show that oil prices have short-run causality with all the variables, that is, GDP, unemployment, industrial output, inflation, exchange rate and stock market prices, while they have a long association with inflation, industrial production and unemployment. Further we find a negative relationship between oil prices and unemployment, industrial output, inflation and exchange rate and a positive relationship with GDP and stock prices.


2020 ◽  
Vol 12 (2) ◽  
pp. 189-198
Author(s):  
Aastha Khera ◽  
◽  
Neelam Dhanda ◽  

This existing study aims to investigate the relationship between Indian Bankingstock market prices and macroeconomic variables. The proxy for the Indian Banking stockmarket is Nifty Bank while Foreign Reserve, Exchange Rate (Indian vs US Dollar), Interestrate, and CPI are proxies of macroeconomic variables. Johansen Cointegration and VectorError Correction Model (VECM) on monthly data from January 2013 to July 2020 have beenapplied. Considering the results of cointegration, it is found that there is a long-run asso-ciation between the Indian Banking stock market and constituent macroeconomic variables.Next, the employment of VECM is done for inspecting long run and short-run causality.The result reveals long-run equilibrium in Indian commercial bankís stock prices comingfrom macroeconomic variables. This study has considerable imputations that investors candiversify their portfolio according to the ináuencing power of constituent selected macro-economic variables in the short run and the long run. Exchange rate and foreign reservesdrive the banking stock market in the short run whereas CPI and Interest rate do not createany signiÖcant impact.


2015 ◽  
Vol 7 (5(J)) ◽  
pp. 6-18
Author(s):  
Erhan Cankal

Financial sector is considered to be important in signaling about economic development. It is a common belief that stock market returns contain significant information on economic well-being and act as a good source of market indicator in a country. This common belief is tested for a number of countries using various methods in literature. Whether stock market returns are affected by changes in primary macroeconomic variables have been tested for different time periods in many countries. The findings of the previous studies proved that the results may vary depending on country specific characteristics. The directions and magnitudes of the examined relationships seemed to be different for various economies. However, the mainstream of the findings is consistent with theoretical expectations. This study attempts to bring a light to the relationship between stock market returns and basic macroeconomic variables using monthly data between 2003 and 2015 and employing structural vector autoregressive (SVAR) model for the Turkish economy. Turkey is considered as one of the most vulnerable five countries whose stock prices are most responsive to, exchange rate shocks. This study concludes that the stock prices in Turkey responsive to the shocks in exchange rate, interest rate, and inflation in order. The results of the analyses are in accordance with theoretical expectations as well as with the findings of the vast majority in the literature.


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