The stock market and the business cycle in South Africa
- Authors: Pokoo, Patience
- Date: 2024-10-11
- Subjects: Stock exchanges South Africa , Economic activity , Business cycles South Africa , Autoregression (Statistics) , Policymaker , Johannesburg Stock Exchange
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/462801 , vital:76336
- Description: The relationship between the stock market and economic activity has long been a topic for research. Several studies done in both advanced and emerging economies including South Africa before COVID-19 found stock market prices predict the cycle of real economic activity and some found it to be the reversal. Therefore, this Study seeks to examine this topic and will extend beyond the post-covid period exploring the relationship between the stock market (proxied by the JSE All-Share Index) and the business cycle (represented by the Coincident Business Cycle Indicator of the SARB) in South Africa. The study also investigates if the relationship between the stock market and the business cycle is homogenous across the three selected sectors of the JSE using a combination of the “financial accelerator theory”, the “wealth effect theory”, the “traditional valuation model of stock prices”, the “stock prices as aggregators of expectations”, and the “cost of raising equity capital”. The Econometrics models employed include time-series and panel cointegration techniques, relying on the ARDL estimation model and a Granger-Causality Test. The findings of this study indicate that a long-run relationship exists between the stock market and the business cycle in South Africa. The findings support the notion that the stock market predicts economic activity, and this relationship is assumed to be homogenous across the selected Sectors of the JSE (namely, Resources, Financials, and Industrials). Again, the Granger-Causality Test confirms the relationship between the stock market and the business cycle in South Africa to be unidirectional. It is recommended that since the stock market affects South African economic activity positively in the long run which is consistent with findings of similar studies done on the JSE, the South African Reserve Bank (SARB) must strengthen existing policy to ensure financial system stability and sustainable economic growth in South Africa. Again, the stock market being a leading indicator of the business cycle is something different. As a recommendation, we need to look at ways to use the prediction ability in a business setting. Investors and Portfolio Managers can follow trends of the stock market to forecast the direction of the future economy to make educated decisions to hedge their investments and diversify their portfolios against huge losses in crises such as the Financial Crises and the Global Health Crisis (COVID-19), however, with the caveat that the stock market does not always accurately predict the business cycle. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2024
- Full Text:
- Date Issued: 2024-10-11
- Authors: Pokoo, Patience
- Date: 2024-10-11
- Subjects: Stock exchanges South Africa , Economic activity , Business cycles South Africa , Autoregression (Statistics) , Policymaker , Johannesburg Stock Exchange
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/462801 , vital:76336
- Description: The relationship between the stock market and economic activity has long been a topic for research. Several studies done in both advanced and emerging economies including South Africa before COVID-19 found stock market prices predict the cycle of real economic activity and some found it to be the reversal. Therefore, this Study seeks to examine this topic and will extend beyond the post-covid period exploring the relationship between the stock market (proxied by the JSE All-Share Index) and the business cycle (represented by the Coincident Business Cycle Indicator of the SARB) in South Africa. The study also investigates if the relationship between the stock market and the business cycle is homogenous across the three selected sectors of the JSE using a combination of the “financial accelerator theory”, the “wealth effect theory”, the “traditional valuation model of stock prices”, the “stock prices as aggregators of expectations”, and the “cost of raising equity capital”. The Econometrics models employed include time-series and panel cointegration techniques, relying on the ARDL estimation model and a Granger-Causality Test. The findings of this study indicate that a long-run relationship exists between the stock market and the business cycle in South Africa. The findings support the notion that the stock market predicts economic activity, and this relationship is assumed to be homogenous across the selected Sectors of the JSE (namely, Resources, Financials, and Industrials). Again, the Granger-Causality Test confirms the relationship between the stock market and the business cycle in South Africa to be unidirectional. It is recommended that since the stock market affects South African economic activity positively in the long run which is consistent with findings of similar studies done on the JSE, the South African Reserve Bank (SARB) must strengthen existing policy to ensure financial system stability and sustainable economic growth in South Africa. Again, the stock market being a leading indicator of the business cycle is something different. As a recommendation, we need to look at ways to use the prediction ability in a business setting. Investors and Portfolio Managers can follow trends of the stock market to forecast the direction of the future economy to make educated decisions to hedge their investments and diversify their portfolios against huge losses in crises such as the Financial Crises and the Global Health Crisis (COVID-19), however, with the caveat that the stock market does not always accurately predict the business cycle. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2024
- Full Text:
- Date Issued: 2024-10-11
Yield curve and business cycle dynamics in South Africa: new evidence from a Markov switching model
- Authors: Rotich, Mercyline Chepkemoi
- Date: 2024-04-03
- Subjects: Yield curve , Business cycles South Africa , Markov processes , Recessions South Africa , Multivariate analysis
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/434739 , vital:73101
- Description: Globally, several empirical studies have demonstrated the ability of the yield spread to predict a recession in a country. In South Africa, previous studies have not only shown the yield curve's predictive power but have further demonstrated that it outperforms other commonly used variables, such as the growth rate of real money supply, changes in stock prices, and the index of leading economic indicators. However, some recent studies have shown that the yield spread (the spread between 10-year bonds and 3-month Treasury bills) gave false signals of recession. In this study, we explore the possible reasons for the false signals of the yield spread by addressing the following questions. Does the yield spread used matter? Does the measure of the business cycle used matter? And do the estimation techniques used matter? To address the first question, unlike the previous studies, this paper uses four different yield spreads- depicting short-term, medium-term, and long-term government bonds against the backdrop of a changing structure of bond holding, which reflects the increasing risk eversion of investors in South Africa. Second, the paper used different measures of business cycles, namely industrial production index, lagging, coincident, and leading economic indicators. The empirical models were estimated using both univariate and multivariate Markov switching models. As economic theory suggests, the univariate Markov switching model was used to determine if each variable exhibits a significant regime switching. The multivariate Markov switching model was estimated for each business cycle and yield spread variable, with each of the other variables serving as a non-switching explanatory variable, thereby addressing potential endogeneity concerns and the predictive power of the explanatory variable. Finally, the multivariate Markov switching model was estimated for three monthly sample periods, a full sample for 1986 to 2022, and two sub-samples – 1986 to 2009 and 2010 to 2022. This analysis consistently reveals significant regime-switching behavior across all the series thus, affirming the superiority of the regime switching model over the standard model used in previous studies. By analyzing the transition probabilities and the expected durations between these regimes, we find that including the spreads in the business cycle model improves the models’ predictability, with the medium-term bonds spread performing better than the usual long-term spread. The smoothed regime probability of the best-performing models is compared with the SARB recession dates; the two closely resemble each other, proving that the Markov switching model can help predict the turning points in the business cycle in South Africa. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2024
- Full Text:
- Date Issued: 2024-04-03
- Authors: Rotich, Mercyline Chepkemoi
- Date: 2024-04-03
- Subjects: Yield curve , Business cycles South Africa , Markov processes , Recessions South Africa , Multivariate analysis
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/434739 , vital:73101
- Description: Globally, several empirical studies have demonstrated the ability of the yield spread to predict a recession in a country. In South Africa, previous studies have not only shown the yield curve's predictive power but have further demonstrated that it outperforms other commonly used variables, such as the growth rate of real money supply, changes in stock prices, and the index of leading economic indicators. However, some recent studies have shown that the yield spread (the spread between 10-year bonds and 3-month Treasury bills) gave false signals of recession. In this study, we explore the possible reasons for the false signals of the yield spread by addressing the following questions. Does the yield spread used matter? Does the measure of the business cycle used matter? And do the estimation techniques used matter? To address the first question, unlike the previous studies, this paper uses four different yield spreads- depicting short-term, medium-term, and long-term government bonds against the backdrop of a changing structure of bond holding, which reflects the increasing risk eversion of investors in South Africa. Second, the paper used different measures of business cycles, namely industrial production index, lagging, coincident, and leading economic indicators. The empirical models were estimated using both univariate and multivariate Markov switching models. As economic theory suggests, the univariate Markov switching model was used to determine if each variable exhibits a significant regime switching. The multivariate Markov switching model was estimated for each business cycle and yield spread variable, with each of the other variables serving as a non-switching explanatory variable, thereby addressing potential endogeneity concerns and the predictive power of the explanatory variable. Finally, the multivariate Markov switching model was estimated for three monthly sample periods, a full sample for 1986 to 2022, and two sub-samples – 1986 to 2009 and 2010 to 2022. This analysis consistently reveals significant regime-switching behavior across all the series thus, affirming the superiority of the regime switching model over the standard model used in previous studies. By analyzing the transition probabilities and the expected durations between these regimes, we find that including the spreads in the business cycle model improves the models’ predictability, with the medium-term bonds spread performing better than the usual long-term spread. The smoothed regime probability of the best-performing models is compared with the SARB recession dates; the two closely resemble each other, proving that the Markov switching model can help predict the turning points in the business cycle in South Africa. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2024
- Full Text:
- Date Issued: 2024-04-03
Long Waves of Strikes in South Africa: 1886–2019
- Authors: Cottle, Eddie
- Date: 2020
- Subjects: Strikes and lockouts South Africa , Long waves (Economics) South Africa , Business cycles South Africa , Industrial mobilization South Africa , Collective bargaining South Africa , Institutionalisation , Labor unions South Africa
- Language: English
- Type: thesis , text , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/163228 , vital:41020 , doi:10.21504/10962/163228
- Description: Thesis (PhD)--Rhodes University, Faculty of Humanities, Institute for Social and Economic Research (ISER), 2020.
- Full Text:
- Date Issued: 2020
- Authors: Cottle, Eddie
- Date: 2020
- Subjects: Strikes and lockouts South Africa , Long waves (Economics) South Africa , Business cycles South Africa , Industrial mobilization South Africa , Collective bargaining South Africa , Institutionalisation , Labor unions South Africa
- Language: English
- Type: thesis , text , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/163228 , vital:41020 , doi:10.21504/10962/163228
- Description: Thesis (PhD)--Rhodes University, Faculty of Humanities, Institute for Social and Economic Research (ISER), 2020.
- Full Text:
- Date Issued: 2020
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