Authors :
Morris Emmanuel Dzingai
Volume/Issue :
Volume 8 - 2023, Issue 7 - July
Google Scholar :
https://tinyurl.com/yv597b9f
Scribd :
https://tinyurl.com/385tde4c
DOI :
https://doi.org/10.5281/zenodo.10154304
Abstract :
This study investigates the nexus between the
Botswana stock index and five macroeconomic variables
which include interest rates, exchange rates, Gross
Domestic product, and Money Supply and inflation
rates. The Botswana stock market and the Bank of
Botswana provided the statistical data for this study.
This study set out to determine whether there were any
correlations between macroeconomic factors and the
behaviour of stock prices in the financial market for
long-term sources of funds traded on the Botswana Stock
exchange (BSE). The paper examines the causal
relationship between the stock prices and five
macroeconomic variables, including the inflation rate,
risk free interest rate, Gross Domestic Product, Money
supply and exchange rates for Botswana, using monthly
data from January 2013 to December 2015. This study
used statistical analysis to create a regression equation
and discovered negative links between three independent
variables and the Botswana domestic stock index as well
as positive relationships between historical and current
domestic stock returns. The study initially took into
account the Stationarity test and found that all of the
variables at the second level at the 1%, 5%, and 10%
level of test are stationary. This study's findings agreed
with those of a number of other studies, which found
that these three macroeconomic factors are linked to
domestic stock indices and both had a negative impact
on the benchmark stock index, or BSI. A unidirectional
link between the domestic stock index and the inflation
rate, exchange rate, and prime rate was demonstrated by
the Augmented Dickey Fuller test (ADF). Another
finding of this study was that the parameters utilised are
significant when the p-values are smaller than the test
statistics at 0.1. This study suggests that additional
research be done over a longer time period, on average,
twenty years, using a variety of other macroeconomic
indicators. The macroeconomic variables that will be
used should include this variable as well.
This study investigates the nexus between the
Botswana stock index and five macroeconomic variables
which include interest rates, exchange rates, Gross
Domestic product, and Money Supply and inflation
rates. The Botswana stock market and the Bank of
Botswana provided the statistical data for this study.
This study set out to determine whether there were any
correlations between macroeconomic factors and the
behaviour of stock prices in the financial market for
long-term sources of funds traded on the Botswana Stock
exchange (BSE). The paper examines the causal
relationship between the stock prices and five
macroeconomic variables, including the inflation rate,
risk free interest rate, Gross Domestic Product, Money
supply and exchange rates for Botswana, using monthly
data from January 2013 to December 2015. This study
used statistical analysis to create a regression equation
and discovered negative links between three independent
variables and the Botswana domestic stock index as well
as positive relationships between historical and current
domestic stock returns. The study initially took into
account the Stationarity test and found that all of the
variables at the second level at the 1%, 5%, and 10%
level of test are stationary. This study's findings agreed
with those of a number of other studies, which found
that these three macroeconomic factors are linked to
domestic stock indices and both had a negative impact
on the benchmark stock index, or BSI. A unidirectional
link between the domestic stock index and the inflation
rate, exchange rate, and prime rate was demonstrated by
the Augmented Dickey Fuller test (ADF). Another
finding of this study was that the parameters utilised are
significant when the p-values are smaller than the test
statistics at 0.1. This study suggests that additional
research be done over a longer time period, on average,
twenty years, using a variety of other macroeconomic
indicators. The macroeconomic variables that will be
used should include this variable as well.
