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The dynamic relationship between exchange rates and stock market trends in Tanzania

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The purpose of this study was to analyse the impact of the exchange rate on stock market prices in Tanzania. The study used Stock Index Prices data of all firms listed at the Dar es Salaam Stock Exchange Market, and the Exchange Rate data were collected from the Bank of Tanzania website. The research used data from 2020 to 2024 to capture recent post-pandemic dynamics. The research used a descriptive case-based study design that allowed for a quantitative data analysis. In addition, the study included the analysis of other macroeconomic variables such as Gross Domestic Product [GDP] and inflation as control variables. The Granger Sim Causality Test was used to test the direction of the relationship between the exchange rate and stock market prices. The Unrestricted Vector Autoregressive Model was used to analyse the impact of the exchange rate on stock market prices after exhibiting the absence of co-integration among the variables. The other model used to test the robustness of the unrestricted VAR was the ARIMA model. The results show that there is a positive unidirectional relationship between exchange rate and stock market prices, with a causation running from exchange rate to stock market prices using the Granger causality test. The results of the study reveal that the average stock index was 2298.79, and it was 1898.472, 5.437, and 5.93 for exchange rate, GDP, and inflation, respectively. The correlation between stock prices and the exchange rate of a dollar against Tanzanian shillings was 0.228, which was a positive correlation. The regression analysis using the OLS shows a positive relationship between the exchange rate and stock market prices. The relationship was found to be statistically significant because the p-value < 0.05 at 95%. The graphical trend analysis shows that there is a co-movement between the exchange rate and stock market prices. The relationship between exchange rate and stock market prices was further examined using an unrestricted Vector Autoregressive Model, and similar results confirmed that there is a positive association between the two variables. The model was tested for stability, and it was found to be stable, as all variables lay within the unit root. It found that there is no long-run association between the exchange rate and stock price as tested by using the co-integration test. The analysis will help authorities in the capital markets formulate policies and analyse their investments to increase their wealth and explore better ways to stabilise the economy. On the other hand, the Bank of Tanzania and other monetary authorities should make stronger policies to keep exchange rates stable. Also, investors, portfolio managers, and stockbrokers should all include changes in exchange rates in their investment analysis and portfolio management plans. By keeping an eye on foreign exchange trends, investors can use this information to guess how the stock market might change.
Title: The dynamic relationship between exchange rates and stock market trends in Tanzania
Description:
The purpose of this study was to analyse the impact of the exchange rate on stock market prices in Tanzania.
The study used Stock Index Prices data of all firms listed at the Dar es Salaam Stock Exchange Market, and the Exchange Rate data were collected from the Bank of Tanzania website.
The research used data from 2020 to 2024 to capture recent post-pandemic dynamics.
The research used a descriptive case-based study design that allowed for a quantitative data analysis.
In addition, the study included the analysis of other macroeconomic variables such as Gross Domestic Product [GDP] and inflation as control variables.
The Granger Sim Causality Test was used to test the direction of the relationship between the exchange rate and stock market prices.
The Unrestricted Vector Autoregressive Model was used to analyse the impact of the exchange rate on stock market prices after exhibiting the absence of co-integration among the variables.
The other model used to test the robustness of the unrestricted VAR was the ARIMA model.
The results show that there is a positive unidirectional relationship between exchange rate and stock market prices, with a causation running from exchange rate to stock market prices using the Granger causality test.
The results of the study reveal that the average stock index was 2298.
79, and it was 1898.
472, 5.
437, and 5.
93 for exchange rate, GDP, and inflation, respectively.
The correlation between stock prices and the exchange rate of a dollar against Tanzanian shillings was 0.
228, which was a positive correlation.
The regression analysis using the OLS shows a positive relationship between the exchange rate and stock market prices.
The relationship was found to be statistically significant because the p-value < 0.
05 at 95%.
The graphical trend analysis shows that there is a co-movement between the exchange rate and stock market prices.
The relationship between exchange rate and stock market prices was further examined using an unrestricted Vector Autoregressive Model, and similar results confirmed that there is a positive association between the two variables.
The model was tested for stability, and it was found to be stable, as all variables lay within the unit root.
It found that there is no long-run association between the exchange rate and stock price as tested by using the co-integration test.
The analysis will help authorities in the capital markets formulate policies and analyse their investments to increase their wealth and explore better ways to stabilise the economy.
On the other hand, the Bank of Tanzania and other monetary authorities should make stronger policies to keep exchange rates stable.
Also, investors, portfolio managers, and stockbrokers should all include changes in exchange rates in their investment analysis and portfolio management plans.
By keeping an eye on foreign exchange trends, investors can use this information to guess how the stock market might change.

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