A Study of the Effect of Inflation and Exchange Rate on Stock Market Returns in Ghana

Kwofie, Charles; Ansah, Richard Kwame

doi:10.1155/2018/7016792

Cited by 64 publications

(64 citation statements)

References 7 publications

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“…The study uses annual time series data covering the period 2000 to 2015 and employs GARCH (1, 1) for the estimation. The study reveals a negative relationship between exchange rate volatility and stock market which is consistent with the study by Kwofie and Ansah (2018). Kwofie and Ansah (2018) examine the effect of inflation and exchange rate on stock market returns in Ghana using monthly data from January 2000 to December 2013.…”

Section: Literature Reviewsupporting

confidence: 85%

“…The study reveals a negative relationship between exchange rate volatility and stock market which is consistent with the study by Kwofie and Ansah (2018). Kwofie and Ansah (2018) examine the effect of inflation and exchange rate on stock market returns in Ghana using monthly data from January 2000 to December 2013. The results from the autoregressive distributed lag model show that there is a positive relationship between inflation and stock market returns and a negative relationship between exchange rate and stock market returns.…”

Section: Literature Reviewsupporting

confidence: 85%

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The Effect of Exchange Rate and Interest Rate Volatilities on Stock Prices: Further Empirical Evidence from Ghana

Ofori-Abebrese

Baidoo

Osei³

2019

Elit

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Studies have proven that volatilities in the rates of exchange and interest influence the performance of institutions and the values of their shares. This study investigates empirically the effect of exchange rate and interest rate volatilities on stock prices of financial institutions listed on the Ghana Stock Exchange using monthly data spanning the period January 2000 to October 2016. The generalized autoregressive conditional heteroskedastic (GARCH) model is employed for the analysis. The results show that exchange rate volatility exerts a positive effect on stock prices whereas interest rate volatility impacts on stock prices negatively. These results imply that the trade-off between risk and return can be predicted so industry players and stakeholders can manage risk to ensure a vibrant financial market. It is also suggested that there is a need for stakeholders and policymakers to ensure that these variables are stable or the volatilities are minimized in the economy. This will go a long way to enhance the performance of the stock market activities in the country.

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Section: Literature Reviewsupporting

confidence: 85%

Section: Literature Reviewsupporting

confidence: 85%

The Effect of Exchange Rate and Interest Rate Volatilities on Stock Prices: Further Empirical Evidence from Ghana

Ofori-Abebrese

Baidoo

Osei³

2019

Elit

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“…Buying rate, value for purchasing foreign exchange, 4. Flat rate, rate normally used in the traveler check purchase of a or bank note (Fischer, Lieberman, & Adams, 1981) The exchange rate (exchange rate) along with the inflation rate have a longterm relationship with the stock returns (Kwofie & Ansah, 2018). The exchange rate is also the most important indicator of a country's economic growth.…”

Section: Exchange Ratementioning

confidence: 99%

The Effect of Transfering Israel Capital City to Jerusalem Toward Indonesia Macro Economy

Sulistiyowati

2020

EKUITAS

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United States President, Donald Trump, issued a controversial policy recognizing Jerusalem as the Capital of Israel. The political impact of these policies has an impact on the global economy. World stock exchanges immediately reacted, including the fall of stock exchanges in Asia. The impact of these policies also impacted the Indonesian economy. The policy triggered an increase in the exchange rate of US$ against the Rupiah. Another negative effect is the increase in world crude oil prices. The increase in world crude oil prices impose a fiscal burden on the state budget. The fuel subsidy in the state budget has increased along with the increase in world crude oil prices. The policy also affects the inflation rate and SBI. Throughout 2018, Bank Indonesia has raised SBIs by 150 basis points or 1.5%. Determination of high SBI has an effect to reduce inflationary pressures. This study aims to look at the effect of moving the Israeli capital to Jerusalem on Indonesian macroeconomic variables, namely the inflation rate, SBI and the exchange rate of the rupiah against US $. Oneway ANOVA method was used as the method of analysis in this study. The research data used is the monthly report of Bank Indonesia from January 2017 to December 2018. The research results obtained are that there is an influence of the move of the Capital of Israel to Jerusalem on Indonesian macroeconomic indicators, namely the inflation rate, SBI and the exchange rate of the rupiah against US$.

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“…In Ghana, some researchers' attempted to examine the association between MVs and stock-price on the Ghana Stock Exchange (GSE). Using the Autoregressive Distributed Lag Model (ARDL) and error correction parameterisation techniques, a significant relationship between MVs (exchange-rate, inflation-rate, and interestrate) and stock returns in Ghana was discovered by (Kwofie and Ansah, 2018). A contrary short-run, decisive long-term, and unidirectional causality from inflation to stocks return in Ghana using VECM were revealed by (Issahaku et al, 2013).…”

Section: Economic Variables and Stock Marketmentioning

confidence: 99%

Random Forest Based Feature Selection of Macroeconomic Variables for Stock Market Prediction

Nti

Adekoya

Weyori

2019

American Journal of Applied Sciences

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A firm's equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), Autoregressive Moving Average (ARMA) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH). However, these techniques are reported to suffer from limited predictive power and restrictive assumptions. Besides, in pursuit of ways to remedy these paucities and limitations within these techniques, some researchers have examined uncountable machine learning techniques for measuring the stock-markets trends and making trading decisions using macroeconomic variables. On the other hand, a higher percentage of these studies paid attention to the stock index prediction and neglected the diversity of MVs that influence different sector indices. In addressing the issues above, this study seeks to examine the degree of significance between different sectors stock-price and MVs and predict a 30-day head stock-price using Random Forest (RF) with an improve leave-one-out cross-validation tactic and Long Short-Term Memory Recurrent Neural Network (LSTMRNN). An empirical analysis of the proposed model over the Ghana Stock Exchange (GSE) exhibits high prediction accuracy and better mean absolute error compared with other time-series techniques. It can, therefore, be inferred from the fallouts that the proposed stock-market prediction with MVs, provides an efficient approach to automatic identification and extraction of MVs that affect diverse sector stock and offer an accurate prediction of a stock's future price.

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A Study of the Effect of Inflation and Exchange Rate on Stock Market Returns in Ghana

Cited by 64 publications

References 7 publications

The Effect of Exchange Rate and Interest Rate Volatilities on Stock Prices: Further Empirical Evidence from Ghana

The Effect of Exchange Rate and Interest Rate Volatilities on Stock Prices: Further Empirical Evidence from Ghana

The Effect of Transfering Israel Capital City to Jerusalem Toward Indonesia Macro Economy

Random Forest Based Feature Selection of Macroeconomic Variables for Stock Market Prediction

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