The status quo of East African stock markets: Integration and volatility

Abstract

This paper presents the current stock markets' situation of East African markets compared to Johannesburg Stock Exchange (JSE). The study uses weekly price indices of Kenya, Tanzania, Rwanda, and Uganda, South Africa as a performance benchmark for the African market. The period used is from 17th January 2008 to 31st March 2017. The stock indices' returns results show in general that there is relatively moderate-to-low volatility. The Dares -Salaam stock index and the Johannesburg stock index show a higher volatility relative to the other stock market indices with the JSE showing the highest return of 0.117089 when compared to the East African market indices. The Vector Autoregressive (VAR) and Granger causality results capture the linear interdependencies among the given markets and illustrate that JSE has a low contributory impact on the returns on the East African markets. Besides, evidence shows that East African markets are independent, thus offering regional diversification benefits. However, integration is still underway.

The Role of Macroeconomic Variables in Forecasting Equity Market Volatility in the East African Community Using Garch-Midas Model

“…Utilizing various univariate specifications of GARCH type models, (Maqsood et al, 2017) aimed to model stock returns volatility for Kenya's Nairobi Securities Exchange (NSE), the study found that the TGARCH (1,1) model was more appropriate in terms of capturing the presence of volatility clustering and the leverage effect on the NSE. While using the Vector Autoregressive (VAR) and Granger causality, (Marselline, 2019) studied the interdependencies among East African markets in relation to Johannesburg Stock Exchange (JSE), the study found that JSE has a low contributory impact on the returns on the East African markets.…”

“…While existing literature has delved into the study of equity market volatility within individual East African countries (Maqsood et al, 2017;Marselline, 2019;Namugaya et al, 2014Namugaya et al, , 2019, a significant research gap lies in the absence of a comparative analysis across these nations. Moreover, none of the current studies have harnessed the potential of the GARCH-MIDAS model, which uniquely allows the incorporation of crucial macroeconomic variables into equity market volatility forecasting.…”

The Role of Macroeconomic Variables in Forecasting Equity Market Volatility in the East Aftican Community

“…While existing literature has delved into studying equity market volatility within individual East African countries (Maqsood et al, 2017;Marselline, 2019;Namugaya et al, 2014Namugaya et al, , 2019, a significant research gap lies in the absence of a comparative analysis across these nations. Moreover, none of the current studies has harnessed the potential of the GARCH MIDAS model, which uniquely allows the incorporation of crucial macroeconomic variables into equity market volatility forecasting.…”

Stock market integration in Africa: Further evidence from an information‐theoretic framework

“…Alagidede (2009) rather points to the irrelevance of geographic and economic ties in the integration of the African market. Atenya (2019) examines the flow of information between the Johannesburg Stock Exchange (JSE) and the East African exchanges of Uganda, Tanzania, Kenya and Rwanda. Using a data set of stock index prices of the five countries between 17 January 2008 and 31 March 2017, this study finds no evidence of the JSE influencing the returns of the East African exchanges.…”